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social network is included as keyword or extra keyword in 0 datasets, 0 tools and 71 publications.
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|Title||Author(s)||Published in||Language||DateThis property is a special property in this wiki.||Abstract||R||C|
|A social network system for sharing construction safety and health knowledge||Le Q.T.
|Automation in Construction||English||2014||Due to the complicated and complex working environments, construction site still presents high accident rate, which is causing serious project delay and cost overrun. Abundant studies have focused on cause and effect on fatalities or safety training system, and so on. Most of them on this issue have been emphasized the necessity and utilization of information, rather than how to exchange, share and transfer safety data efficiently in the construction industry. With this regard, this paper proposes the Social Network System for Sharing Construction Safety & Health Knowledge (SNSS), which utilizes state-of-the-art of semantic wiki web and ontology construction technologies for better communication and representation for construction safety information. The SNSS is developed on the basis of safety semantic wiki template (SSWT), which consists of the following three modules: 1) A Safety information module (SIM) which upload common accident and hazard information for sharing; 2) A Safety knowledge module (SKM) where the safety information is refined, confirmed and transferred to safety knowledge; 3) A Safety dissemination module (SDM) which allows its users to monitor, manage and retrieve safety information and knowledge easily. The SNSS is tested by a scenario of using falling accident information by which the potentials and limitations of the system were addressed. The study emphasizes the potential applicability and benefits of social network system that could be utilized to enhance communication among participants in the construction industry. © 2014 Elsevier B.V.||0||0|
|Bipartite editing prediction in wikipedia||Chang Y.-J.
|Journal of Information Science and Engineering||English||2014||Link prediction problems aim to project future interactions among members in a social network that have not communicated with each other in the past. Classical approaches for link prediction usually use local information, which considers the similarity of two nodes, or structural information such as the immediate neighborhood. However, when using a bipartite graph to represent activity, there is no straightforward similarity measurement between two linking nodes. However, when a bipartite graph shows two nodes of different types, they will not have any common neighbors, so the local model will need to be adjusted if the users' goal is to predict bipartite relations. In addition to local information regarding similarity, when dealing with link predictions in a social network, it is natural to employ community information to improve the prediction accuracy. In this paper, we address the link prediction problem in the bipartite editing graph used in Wikipedia and also examine the structure of community in this edit graph. As Wikipedia is one of the successful member-maintained online communities, extracting the community information and solving its bipartite link prediction problem will shed light on the process of content creation. In addition, to the best of our knowledge, the problem of using community information in bipartite for predicting the link occurrence has not been clearly addressed. Hence we have designed and integrated two bipartite-specific approaches to predict the link occurrence: First, the supervised learning approach, which is built around the adjusted features of a local model and, second, the community-awareness approach, which utilizes community information. Experiments conducted on the Wikipedia collection show that in terms of F1-measure, our approaches generates an 11% improvement over the general methods based on the K-Nearest Neighbor. In addition to this, we also investigate the structure of communities in the editing network and suggest a different approach to examining the communities involved in Wikipedia.||0||0|
|Experimental Implementation of a M2M System Controlled by a Wiki Network||Takashi Yamanoue
|Applied Computing and Information Technology, Studies in Computational Intelligence||English||2014||Experimental implementation of a M2M system, which is controlled by a wiki network, is discussed. This M2M system consists of mobile terminals at remote places and wiki servers on the Internet. A mobile terminal of the system consists of an Android terminal and it may have an Arduino board with sensors and actuators. The mobile terminal can read data from not only the sensors in the Arduino board but also wiki pages of the wiki servers. The mobile terminal can control the actuators of the Arduino board or can write sensor data to a wiki page. The mobile terminal performs such reading writing and controlling by reading and executing commands on a wiki page, and by reading and running a program on the wiki page, periodically. In order to run the program, the mobile terminal equipped with a data processor. After placing mobile terminals at remote places, the group of users of this system can control the M2M system by writing and updating such commands and programs of the wiki network without going to the places of the mobile terminals. This system realizes an open communication forum for not only people but also for machines .||3||0|
|La connaissance est un réseau: Perspective sur l’organisation archivistique et encyclopédique||Martin Grandjean||Les Cahiers du Numérique||French||2014||Network analysis is not revolutionizing our objects of study, it revolutionizes the perspective of the researcher on the latter. Organized as a network, information becomes relational. It makes potentially possible the creation of new information, as with an encyclopedia which links between records weave a web which can be analyzed in terms of structural characteristics or with an archive directory which sees its hierarchy fundamentally altered by an index recomposing the information exchange network within a group of people. On the basis of two examples of management, conservation and knowledge enhancement tools, the online encyclopedia Wikipedia and the archives of the Intellectual Cooperation of the League of Nations, this paper discusses the relationship between the researcher and its object understood as a whole.
Abstract (french)L’analyse de réseau ne transforme pas nos objets d’étude, elle transforme le regard que le chercheur porte sur ceux-ci. Organisée en réseau, l’information devient relationnelle. Elle rend possible en puissance la création d’une nouvelle connaissance, à l’image d’une encyclopédie dont les liens entre les notices tissent une toile dont on peut analyser les caractéristiques structurelles ou d’un répertoire d’archives qui voit sa hiérarchie bouleversée par un index qui recompose le réseau d’échange d’information à l’intérieur d’un groupe de personnes. Sur la base de deux exemples d’outils de gestion, conservation et valorisation de la connaissance, l’encyclopédie en ligne Wikipédia et les archives de la coopération intellectuelle de la Société des Nations, cet article questionne le rapport entre le chercheur et son objet compris dans sa globalité. [Version preprint disponible].
|Social software in new product development - State of research and future research directions||Rohmann S.
|20th Americas Conference on Information Systems, AMCIS 2014||English||2014||Product development becomes increasingly collaborative and knowledge-intensive in today's industry. To gain competitive advantage an effective usage of information systems in new product development (NPD) is needed. Social software applications indicate further potential for usage in NPD, the so called "Product Development 2.0", which is poorly understood in research so far. The purpose of this article is to point out the current state of research in this area by means of a literature review, after which research gaps and future research directions are identified. The results indicate that social software applications are suitable to support tasks in all phases of the NPD process, but influencing factors and effects of the identified social software usage in NPD are poorly understood so far.||0||0|
|Demonstration of a Loosely Coupled M2M System Using Arduino, Android and Wiki Software||Takashi Yamanoue
|The 38th IEEE Conference on Local Computer Networks (LCN)||English||22 October 2013||A Machine-to-Machine (M2M) system, in which terminals are loosely coupled with Wiki software, is proposed. This system acquires sensor data from remote terminals, processes the data by remote terminals and controls actuators at remote terminals according to the processed data. The data is passed between terminals using wiki pages. Each terminal consists of an Android terminal and an Arduino board. The mobile terminal can be controlled by a series of commands which is written on a wiki page. The mobile terminal has a data processor and the series of commands may have a program which controls the processor. The mobile terminal can read data from not only the sensors of the terminal but also wiki pages on the Internet. The input data may be processed by the data processor of the terminal. The processed data may be sent to a wiki page. The mobile terminal can control the actuators of the terminal by reading commands on the wiki page or by running the program on the wiki page. This system realizes an open communication forum for not only people but also for machines.||8||0|
|A wiki-based assessment system towards social-empowered collaborative learning environment||Kao B.C.
|Lecture Notes in Electrical Engineering||English||2013||The social network has been a very popular research area in the recent years. Lot of people at least have one or more social network account and use it keep in touch with other people on the internet and build own small social network. Thus, the effect and the strength of social network is a very deep and worth to figure out the information delivery path and apply to digital learning area. In this age of web 2.0, sharing knowledge is the main stream of the internet activity, everyone on the internet share and exchanges the information and knowledge every day, and starts to collaborate with other users to build specific knowledge domain in the knowledge database website like Wikipedia. This learning behavior also called co-writing or collaborative learning. This learning strategy brings the new way of the future distance learning. But it is hard to evaluate the performance in the co-writing learning activity, researchers still continue to find out more accurate method which can measure and normalize the learner's performance, provide the result to the teacher, assess the student learning performance in social dimension. As our Lab's previous research, there are several technologies proposed in distance learning area. Based on these background generation, we build a wiki-based website, provide past exam question to examinees, help them to collect all of the target college or license exam resource, moreover, examinees can deploy the question on the own social network, discuss with friends, co-resolve the questions and this system will collect the path of these discussions and analyze the information, improve the collaborative learning assessment efficiency research in social learning field.||0||0|
|Characterizing and curating conversation threads: Expansion, focus, volume, re-entry||Backstrom L.
|WSDM 2013 - Proceedings of the 6th ACM International Conference on Web Search and Data Mining||English||2013||Discussion threads form a central part of the experience on many Web sites, including social networking sites such as Facebook and Google Plus and knowledge creation sites such as Wikipedia. To help users manage the challenge of allocating their attention among the discussions that are relevant to them, there has been a growing need for the algorithmic curation of on-line conversations - - the development of automated methods to select a subset of discussions to present to a user. Here we consider two key sub-problems inherent in conversational curation: length prediction - - predicting the number of comments a discussion thread will receive - - and the novel task of re-entry prediction - - predicting whether a user who has participated in a thread will later contribute another comment to it. The first of these sub-problems arises in estimating how interesting a thread is, in the sense of generating a lot of conversation; the second can help determine whether users should be kept notified of the progress of a thread to which they have already contributed. We develop and evaluate a range of approaches for these tasks, based on an analysis of the network structure and arrival pattern among the participants, as well as a novel dichotomy in the structure of long threads. We find that for both tasks, learning-based approaches using these sources of information.||0||0|
|Communities, artifacts, interaction and contribution on the web||Eleni Stroulia||Lecture Notes in Computer Science||English||2013||Today, most of us are members of multiple online communities, in the context of which we engage in a multitude of personal and professional activities. These communities are supported by different web-based platforms and enable different types of collaborative interactions. Through our experience with the development of and experimentation with three different such platforms in support of collaborative communities, we recognized a few core research problems relevant across all such tools, and we developed SociQL, a language, and a corresponding software framework, to study them.||0||0|
|Competitive Intelligence 2.0 Tools||Deschamps C.||Competitive Intelligence 2.0: Organization, Innovation and Territory||English||2013||[No abstract available]||0||0|
|E-learning and the Quality of Knowledge in a Globalized World||Van De Bunt-Kokhuis S.||Distance and E-Learning in Transition: Learning Innovation, Technology and Social Challenges||English||2013||[No abstract available]||0||0|
|Every move you make I'll be watching you: Geographical focus detection on Twitter||Peregrino F.S.
|Proceedings of the 7th Workshop on Geographic Information Retrieval, GIR 2013||English||2013||On-line Social Networks have increased their popularity rapidly since their creation, providing a huge amount of data which can be leverage to extract useful information related to commercial and social human behaviours. One of the most useful information that can be extracted is the geographical one. This paper shows an approach to detect the geographical focus of Twitter users at city level based on the text of the tweets that users have sent and external information from Wikipedia. The main goal of this work is to show how important could be external formal text resources such as Wikipedia when it comes to resolve the geographical focus in short pieces of informal natural language text. In order to accomplish this objective, we have assessed our system with a language model system, comparing the results using only the informal pieces of text (tweets) and merging it with formal text coming from Wikipedia. In our experiments, we found that the aid of formal pieces of text, such as those obtained from the Wikipedia articles and links, could be useful when the existing amount of data is rather limited.||0||0|
|Hot Off the Wiki: Structures and Dynamics of Wikipedia's Coverage of Breaking News Events||Brian Keegan
|American Behavioral Scientist||English||2013||Wikipedia's coverage of breaking news and current events dominates editor contributions and reader attention in any given month. Collaborators on breaking news articles rapidly synthesize content to produce timely information in spite of steep coordination demands. Wikipedia's coverage of breaking news events thus presents a case to test theories about how open collaborations coordinate complex, time-sensitive, and knowledge-intensive work in the absence of central authority, stable membership, clear roles, or reliable information. Using the revision history from Wikipedia articles about over 3,000 breaking news events, we investigate the structure of interactions between editors and articles. Because breaking article collaborations unfold more rapidly and involve more editors than most Wikipedia articles, they potentially regenerate prior forms of organizing. We analyze whether the structures of breaking and nonbreaking article networks are (a) similarly structured over time, (b) exhibit features of organizational regeneration, and (c) have similar collaboration dynamics over time. Breaking and nonbreaking article exhibit similarities in their structural characteristics over the long run, and there is less evidence of organizational regeneration on breaking articles than nonbreaking articles. However, breaking articles emerge into well-connected collaborations more rapidly than nonbreaking articles, suggesting early contributors play a crucial role in supporting these high-tempo collaborations.||0||0|
|ISICIL: Semantics and social networks for business intelligence||Michel Buffa
|Lecture Notes in Computer Science||English||2013||The ISICIL initiative (Information Semantic Integration through Communities of Intelligence onLine) mixes viral new web applications with formal semantic web representations and processes to integrate them into corporate practices for technological watch, business intelligence and scientific monitoring. The resulting open source platform proposes three functionalities: (1) a semantic social bookmarking platform monitored by semantic social network analysis tools, (2) a system for semantically enriching folksonomies and linking them to corporate terminologies and (3) semantically augmented user interfaces, activity monitoring and reporting tools for business intelligence.||0||0|
|Interest classification of twitter users using wikipedia||Lim K.H.
|Proceedings of the 9th International Symposium on Open Collaboration, WikiSym + OpenSym 2013||English||2013||We present a framework for (automatically) classifying the relative interests of Twitter users using information from Wikipedia. Our proposed framework first usesWikipedia to automatically classify a user's celebrity followings into various interest categories, followed by determining the relative interests of the user with a weighting compared to his/her other interests. Our preliminary evaluation on Twitter shows that this framework is able to correctly classify users' interests and that these users frequently converse about topics that reflect both their (detected) interest and a related real-life event. Categories and Subject Descriptors: J.4 [Computer Applications]: Social and behavioral sciences General Terms: Theory. Copyright 2010 ACM.||0||0|
|MJ no more: Using concurrent wikipedia edit spikes with social network plausibility checks for breaking news detection||Steiner T.
Van Hooland S.
|WWW 2013 Companion - Proceedings of the 22nd International Conference on World Wide Web||English||2013||We have developed an application called Wikipedia Live Monitor that monitors article edits on different language versions of Wikipedia-as they happen in realtime. Wikipedia articles in different languages are highly interlinked. For example, the English article "en:2013 Russian meteor event" on the topic of the February 15 meteoroid that exploded over the region of Chelyabinsk Oblast, Russia, is interlinked with ", the Russian article on the same topic. As we monitor multiple language versions of Wikipedia in parallel, we can exploit this fact to detect concurrent edit spikes of Wikipedia articles covering the same topics, both in only one, and in different languages. We treat such concurrent edit spikes as signals for potential breaking news events, whose plausibility we then check with full-text cross-language searches on multiple social networks. Unlike the reverse approach of monitoring social networks first, and potentially checking plausibility on Wikipedia second, the approach proposed in this paper has the advantage of being less prone to falsepositive alerts, while being equally sensitive to true-positive events, however, at only a fraction of the processing cost. A live demo of our application is available online at the URL http://wikipedia-irc. herokuapp.com/, the source code is available under the terms of the Apache 2.0 license at https://github.com/tomayac/wikipedia-irc.||0||0|
|Manipulation among the arbiters of collective intelligence: How wikipedia administrators mold public opinion||Sanmay Das
|International Conference on Information and Knowledge Management, Proceedings||English||2013||Our reliance on networked, collectively built information is a vulnerability when the quality or reliability of this information is poor. Wikipedia, one such collectively built information source, is often our first stop for information on all kinds of topics; its quality has stood up to many tests, and it prides itself on having a "Neutral Point of View". Enforcement of neutrality is in the hands of comparatively few, powerful administrators. We find a surprisingly large number of editors who change their behavior and begin focusing more on a particular controversial topic once they are promoted to administrator status. The conscious and unconscious biases of these few, but powerful, administrators may be shaping the information on many of the most sensitive topics on Wikipedia; some may even be explicitly infiltrating the ranks of administrators in order to promote their own points of view. Neither prior history nor vote counts during an administrator's election can identify those editors most likely to change their behavior in this suspicious manner. We find that an alternative measure, which gives more weight to influential voters, can successfully reject these suspicious candidates. This has important implications for how we harness collective intelligence: even if wisdom exists in a collective opinion (like a vote), that signal can be lost unless we carefully distinguish the true expert voter from the noisy or manipulative voter. Copyright is held by the owner/author(s).||0||0|
|Motivating and discouraging factors for Wikipedians: The case study of Persian Wikipedia||Asadi S.
|Library Review||English||2013||Purpose: The purpose of this paper is to investigate how Wikipedians are motivated, or discouraged, to contribute to Farsi (Persian) Wikipedia. Design/methodology/approach: In this grounded theory study, face-to-face semi-structured interviews were conducted with a sample of 15 active users of Persian Wikipedia. The interviews then were transcribed and coded using Strauss and Corbin's method which included constant comparison of data. Findings: Editing and writing incentives, as well as deterrents, were extracted from the data. Findings indicated that motivating factors can be classified into two categories of internal and external. Internal motivations could be individual or cognitive motivations or be related to Wikipedia structure. Also, some factors such as permanent access to the internet can be considered as external motivations for contribution to Wikipedia. On the other hand, content production and improvement of Wikipedia in local language was the strongest reason for contribution; entertainment was the weakest motivation. Positive feedback from other users can be the strongest factor that encourages users to stay in Wikipedia and continue their contribution. Originality/value: This is the first study on Persian Wikipedia and one of the few qualitative studies on Wikipedia. It proposes a new categorization of encouraging and discouraging factors for Wikipedians.||0||0|
|Processing Business News for Detecting Firms' Global Networking Strategies||Gay B.||Competitive Intelligence 2.0: Organization, Innovation and Territory||English||2013||[No abstract available]||0||0|
|A M2M system using Arduino, Android and Wiki Software||Takashi Yamanoue
|IIAI ESKM||English||September 2012||A Machine-to-Machine (M2M) system, which uses Arduino, Android, and Wiki software, is discussed. ["proposed"?] This system consists of mobile terminals and web sites with wiki software. A mobile terminal of the system consists of an Android terminal and an Arduino board with sensors and actuators. The mobile terminal reads data from the sensors in the Arduino board and sends the data to a wiki page. The mobile terminal also reads commands on the wiki page and controls the actuators of the Arduino board. In addition, a wiki page can have a program that reads the page and outputs information such as a graph. This system realizes an open communication forum for not only people but also for machines||4||3|
|A M2M system using arduino, android and wiki software||Takashi Yamanoue
|Proceedings of the 2012 IIAI International Conference on Advanced Applied Informatics, IIAIAAI 2012||English||2012||A Machine-to-Machine (M2M) system, which uses Arduino, Android, and Wiki software, is discussed. ["proposed"?] This system consists of mobile terminals and web sites with wiki software. A mobile terminal of the system consists of an Android terminal and an Arduino board with sensors and actuators. The mobile terminal reads data from the sensors in the Arduino board and sends the data to a wiki page. The mobile terminal also reads commands on the wiki page and controls the actuators of the Arduino board. In addition, a wiki page can have a program that reads the page and outputs information such as a graph. This system realizes an open communication forum for not only people but also for machines.||0||3|
|A model for information growth in collective wisdom processes||Sanmay Das
|ACM Transactions on Knowledge Discovery from Data||English||2012||Collaborative media such as wikis have become enormously successful venues for information creation. Articles accrue information through the asynchronous editing of users who arrive both seeking information and possibly able to contribute information. Most articles stabilize to high-quality, trusted sources of information representing the collective wisdom of all the users who edited the article. We propose a model for information growth which relies on two main observations: (i) as an article's quality improves, it attracts visitors at a faster rate (a rich-get-richer phenomenon); and, simultaneously, (ii) the chances that a new visitor will improve the article drops (there is only so much that can be said about a particular topic). Our model is able to reproduce many features of the edit dynamics observed on Wikipedia; in particular, it captures the observed rise in the edit rate, followed by 1/t decay. Despite differences in the media, we also document similar features in the comment rates for a segment of the LiveJournal blogosphere.||0||0|
|Breaking news on Wikipedia: Dynamics, structures, and roles in high-tempo collaboration||Brian C. Keegan||English||2012||The goal of my research is to evaluate how distributed virtual teams are able to use socio-technical systems like Wikipedia to self-organize and respond to complex tasks. I examine the roles Wikipedians adopt to synthesize content about breaking news events out of a noisy and complex information space. Using data from Wikipedia's revision histories as well as from other sources like IRC logs, I employ methods in content analysis, statistical network analysis, and trace ethnography to illuminate the multilevel processes which sustain these temporary collaborations as well as the dynamics of how they emerge and dissolve.||0||0|
|Classifying trust/distrust relationships in online social networks||Bachi G.
|Proceedings - 2012 ASE/IEEE International Conference on Privacy, Security, Risk and Trust and 2012 ASE/IEEE International Conference on Social Computing, SocialCom/PASSAT 2012||English||2012||Online social networks are increasingly being used as places where communities gather to exchange information, form opinions, collaborate in response to events. An aspect of this information exchange is how to determine if a source of social information can be trusted or not. Data mining literature addresses this problem. However, if usually employs social balance theories, by looking at small structures in complex networks known as triangles. This has proven effective in some cases, but it under performs in the lack of context information about the relation and in more complex interactive structures. In this paper we address the problem of creating a framework for the trust inference, able to infer the trust/distrust relationships in those relational environments that cannot be described by using the classical social balance theory. We do so by decomposing a trust network in its ego network components and mining on this ego network set the trust relationships, extending a well known graph mining algorithm. We test our framework on three public datasets describing trust relationships in the real world (from the social media Epinions, Slash dot and Wikipedia) and confronting our results with the trust inference state of the art, showing better performances where the social balance theory fails.||0||0|
|Enhancing networking and proactive learning skills in the first year university experience through the use of wikis||Morley D.A.||Nurse Education Today||English||2012||This paper discusses the introduction of blended learning strategies, a combination of traditional and online techniques, into the first year of a new preregistration nursing advanced diploma and degree programme at Bournemouth University (UK).During a ten week sociology of health academic unit, in the first term of a three year nursing course, wikis were introduced as a complementary learning technique to traditional lectures and seminars. Wikis, an online application, provided eleven student seminar groups (each divided into 4 online or elearning groups of 6-8 students) with the potential to communicate collaboratively "anytime, anywhere" (JISC, 2010) to discuss a sociology preparation activity for the preceding week. The implementation of this elearning tool was structured through the application of Salmon's five stage model (Salmon, 2002) and evaluated from 69 students' online contributions to wikis as well as questionnaires completed by both a sample of students and academic staff. As well as the many comments made by students the evaluation indicated that 45% of students' responses valued wikis as a communication tool and 33% believed it promoted or allowed the sharing of group views.The evaluation presents and critiques the initial project management using Salmon's five stage model and the engagement of students and academic staff. In particular it begins to show how wikis have the potential to structure academic learning and promote social networking in the crucial first few months of a course.||0||0|
|Fluctuations in Wikipedia access-rate and edit-event data||Kampf M.
|Physica A: Statistical Mechanics and its Applications||English||2012||Internet-based social networks often reflect extreme events in nature and society by drastic increases in user activity. We study and compare the dynamics of the two major complex processes necessary for information spread via the online encyclopedia 'Wikipedia', i.e., article editing (information upload) and article access (information viewing) based on article edit-event time series and (hourly) user access-rate time series for all articles. Daily and weekly activity patterns occur in addition to fluctuations and bursting activity. The bursts (i.e., significant increases in activity for an extended period of time) are characterized by a power-law distribution of durations of increases and decreases. For describing the recurrence and clustering of bursts we investigate the statistics of the return intervals between them. We find stretched exponential distributions of return intervals in access-rate time series, while edit-event time series yield simple exponential distributions. To characterize the fluctuation behavior we apply detrended fluctuation analysis (DFA), finding that most article access-rate time series are characterized by strong long-term correlations with fluctuation exponents α≈0.9. The results indicate significant differences in the dynamics of information upload and access and help in understanding the complex process of collecting, processing, validating, and distributing information in self-organized social networks. © 2012 Elsevier B.V. All rights reserved.||0||0|
|Polycystic ovary syndrome: Double click and right check. What do patients learn from the Internet about PCOS?||Mousiolis A.
|European Journal of Obstetrics Gynecology and Reproductive Biology||English||2012||Objective: To identify the websites most visited by patients regarding polycystic ovary syndrome (PCOS), and to evaluate the quality of information provided by these websites. Study design: We sought data regarding the popularity of sites providing information about PCOS regardless of the way the visitors reached the site. We then scrutinized the top sites for predefined quality check points to evaluate the quality of information provided, including Health on Net Foundation (HON) accreditation. Finally, we searched for the expansion of these sites in social networks (Facebook and Twitter). Results: Of the top 15 sites, 8 were HONcode certified. The mean performance of content presence for all sites was 7.33 (min = 4, max = 10, SD = 1.633). There was a moderate correlation of higher performance score with HON accreditation (R: 0.535, p < 0.05). Several sites have expanded in social media. None of the high-score sites has a page dedicated to PCOS. Conclusions: There exists a lack of HON accreditation in many sites and a wide variability in the quality of the information provided. In some cases, key elements of content, necessary for complete appreciation of PCOS, are missing. Official and high authority healthcare organisms should introduce themselves in the social media world. © 2012 Elsevier Ireland Ltd. All rights reserved.||0||0|
|The role of social media in dental education||McAndrew M.
|Journal of Dental Education||English||2012||Social media, also known as Web 2.0, includes a set of web-based technologies in which users actively share and create content through open collaboration. The current students in dental school are Millennial learners who are comfortable using social media, such as Facebook and Twitter, for both socialization and learning. This article defines and explores the range of Web 2.0 technologies available for use in dental education, addresses their underlying pedagogy, and discusses potential problems and barriers to their implementation.||0||0|
|Usage of technology enhanced learning tools and organizational change perception||Cudanov M.
|Computer Science and Information Systems||English||2012||This paper presents an analysis of organizational changes perceived by the employees in the organizations where Technology Enhanced Learning was facilitated by tools such as wiki, (we)blog, Internet forum and social network, practice often considered as E-learning 2.0. Our research focuses on the technologically advanced organizations, leaders in the ICT and IS adoption. We specifically observe the perception of influence on the organizational structure, organizational culture and the knowledge management processes in the organization. Our findings are that the TEL tools are perceived to have a noteworthy impact on the organizational change in the three mentioned areas, and that the perception of change significantly differs depending on whether the employees are regular or are not regular users for organizational structure and knowledge management processes.||0||0|
|Using a wiki-based past exam system to assist co-writing learning assessment with social network||Kao B.C.
|Lecture Notes in Electrical Engineering||English||2012||The social network has been a very popular research area in the recent years. Lot of people at least have one or more social network account and use it keep in touch with other people on the internet and build own small social network. Thus, the effect and the strength of social network is a very deep and worth to figure out the information delivery path and apply to digital learning area. In this age of web 2.0, sharing knowledge is the main stream of the internet activity, everyone on the internet share and exchanges the information and knowledge every day, and starts to collaborate with other users to build specific knowledge domain in the knowledge database website like Wikipedia. This learning behavior also called co-writing or collaborative learning. This learning strategy brings the new way of the future distance learning. But it is hard to evaluate the performance in the co-writing learning activity, researchers still continue to find out more accurate method which can measure and normalize the learner's performance, provide the result to the teacher, assess the student learning performance in social dimension. As our Lab's previous research, there are several technologies proposed in distance learning area. Based on these background generation, we build a wiki-based website, provide past exam question to examinees, help them to collect all of the target college or license exam resource, moreover, examinees can deploy the question on the own social network, discuss with friends, co-resolve the questions and this system will collect the path of these discussions and analyze the information, improve the collaborative learning assessment efficiency research in social learning field.||0||0|
|A Framework for Adopting Collaboration 2.0 Tools for Virtual Group Decision Making||Turban E.
|Group Decision and Negotiation||English||2011||Decision making in virtual teams is gaining momentum due to globalization, mobility of employees, and the need for collective and rapid decision making by members who are in different locations. These factors resulted in a proliferation of virtual team software support tools for decision making, the latest of which is social software (also known as collaboration 2.0), which includes tools such as wikis, blogs, microblogs, discussion forums, and social networking platforms. This paper describes the potential use of collaboration 2.0 software for improving the process and the specific tasks in virtual group decision making. The paper proposes a framework for exploring the fitness between social software and the major activities in the group decision making process and how such tools can be successfully adopted. Specifically, we use a fit-viability model to help assessing whether social software fit a decision task and what organizational factors are important for such tools to be effective. Representative research issues related to the use of such tools are also presented. © 2010 Springer Science+Business Media B.V.||0||0|
|Detecting community kernels in large social networks||Lei Wang
|Proceedings - IEEE International Conference on Data Mining, ICDM||English||2011||In many social networks, there exist two types of users that exhibit different influence and different behavior. For instance, statistics have shown that less than 1% of the Twitter users (e.g. entertainers, politicians, writers) produce 50% of its content , while the others (e.g. fans, followers, readers) have much less influence and completely different social behavior. In this paper, we define and explore a novel problem called community kernel detection in order to uncover the hidden community structure in large social networks. We discover that influential users pay closer attention to those who are more similar to them, which leads to a natural partition into different community kernels. We propose GREEDY and WEBA, two efficient algorithms for finding community kernels in large social networks. GREEDY is based on maximum cardinality search, while WEBA formalizes the problem in an optimization framework. We conduct experiments on three large social networks: Twitter, Wikipedia, and Coauthor, which show that WEBA achieves an average 15%- 50% performance improvement over the other state-of-the-art algorithms, and WEBA is on average 6-2,000 times faster in detecting community kernels.||0||0|
|Extracting multi-dimensional relations: A generative model of groups of entities in a corpus||Au Yeung C.-M.
|International Conference on Information and Knowledge Management, Proceedings||English||2011||Extracting relations among different entities from various data sources has been an important topic in data mining. While many methods focus only on a single type of relations, real world entities maintain relations that contain much richer information. We propose a hierarchical Bayesian model for extracting multi-dimensional relations among entities from a text corpus. Using data from Wikipedia, we show that our model can accurately predict the relevance of an entity given the topic of the document as well as the set of entities that are already mentioned in that document.||0||0|
|Finding hierarchy in directed online social networks||Gupte M.
|Proceedings of the 20th International Conference on World Wide Web, WWW 2011||English||2011||Social hierarchy and stratification among humans is a well studied concept in sociology. The popularity of online social networks presents an opportunity to study social hierarchy for different types of networks and at different scales. We adopt the premise that people form connections in a social network based on their perceived social hierarchy; as a result, the edge directions in directed social networks can be leveraged to infer hierarchy. In this paper, we define a measure of hierarchy in a directed online social network, and present an efficient algorithm to compute this measure. We validate our measure using ground truth including Wikipedia notability score. We use this measure to study hierarchy in several directed online social networks including Twitter, Delicious, YouTube, Flickr, LiveJournal, and curated lists of several categories of people based on different occupations, and different organizations. Our experiments on different online social networks show how hierarchy emerges as we increase the size of the network. This is in contrast to random graphs, where the hierarchy decreases as the network size increases. Further, we show that the degree of stratification in a network increases very slowly as we increase the size of the graph. Copyright © 2011 by the Association for Computing Machinery, Inc. (ACM).||0||0|
|Internet technology-based projects in learning and teaching English as a foreign language at Yakutsk State University||Zamorshchikova L.
|International Review of Research in Open and Distance Learning||English||2011||This paper discusses recent uses of information and communication technologies (ICTs) in fostering Internet-based projects for learning English as a Foreign Language (EFL) at the Faculty of Foreign Languages in Yakutsk State University, Russia. It covers the authors' experiences integrating distance education and creating educational resources within the Moodle LMS and wiki projects based on Web 2.0 social networking technologies. Also it discusses our international project, Net-based Course Development: English through Digital Storyline, in cooperation with the University of Tromsø, Norway.||0||0|
|Knowledge management system for social network services||Chou L.-D.
|Journal of Internet Technology||English||2011||Campus laboratory is a kind of social network. All the members there have similar common sense in the domain of that social network. Members learn knowledge by interaction. Group meeting or exchanging of personal experiences inspires the knowledge innovation. However, social networks face an issue that knowledge cannot be inherited efficiently, even by using Blogs or E-mails. Thus, this paper proposes a knowledge management system (KMS) for social network services: a case study on campus laboratory, in order to inherit experiences of learning efficiently by using knowledge management. Knowledge is not only stored but also used efficiently; we propose Importance Analysis (IA) function for helping knowledge learning. At last, we gave questionnaires for the testing of the proposed system by members in the laboratory, and used the result of the questionnaires indicate that the system is useful for knowledge learning in laboratory.||0||0|
|Oh! Web 2.0, Virtual Reference Service 2.0, Tools & Techniques (I): A Basic Approach||Arya H.B.
|Journal of Library and Information Services in Distance Learning||English||2011||This study targets librarians and information professionals who use Web 2.0 tools and applications with a view to providing snapshots on how Web 2.0 technologies are used. It also aims to identify values and impact that such tools have exerted on libraries and their services, as well as to detect various issues associated with the implementation of Web 2.0 applications in libraries. Offering Web 2.0 tools and technologies to library patrons is also suggested.||0||0|
|Sharing regulatory intelligence: Are newsletters here to stay or is social media the future?||Hynes C.
|Regulatory Rapporteur||English||2011||Regulatory newsletters - electronic or printed - are a key deliverable for the regulatory intelligence (RI) function. In 2009, the Regulatory Intelligence Networking Group (RING)* began a project to review the regulatory newsletters produced by its member companies in order to determine if newsletters are the optimal medium for sharing regulatory intelligence. The RING is also evaluating 'social media' (eg, LinkedIn, Wikipedia, Twitter), as these may offer advantages over newsletters. In utilising social media to enhance the gathering and delivery of regulatory intelligence, there is an excellent opportunity for RI specialists to demonstrate the value of social media to other regulatory affairs professionals. The first part of this article discusses the use of newsletters by RING member companies; the second part explores the current and possible uses of social media to enhance the RI function. Finally, the article considers whether social media will have a future role in the delivery of regulatory intelligence and how RI specialists can demonstrate the value of social media to their colleagues and industry peers.||0||0|
|Social capital increases efficiency of collaboration among Wikipedia editors||Keiichi Nemoto
|Social information systems: Review, framework, and research agenda||Schlagwein D.
|International Conference on Information Systems 2011, ICIS 2011||English||2011||In this research-in-progress, we review the literature on an emerging new type of information systems: social information systems. Social information systems are information systems based on social technologies and open collaboration. The paper provides categories defining social information systems and a framework for existing and future research in this field of study.||0||0|
|Social networks of Wikipedia||Paolo Massa||Hypertext||English||2011||Wikipedia, the free online encyclopedia anyone can edit, is a live social experiment: millions of individuals volunteer their knowledge and time to collective create it. It is hence interesting trying to understand how they do it. While most of the attention concentrated on article pages, a less known share of activities happen on user talk pages, Wikipedia pages where a message can be left for the specific user. This public conversations can be studied from a Social Network Analysis perspective in order to highlight the structure of the “talk” network. In this paper we focus on this preliminary extraction step by proposing different algorithms. We then empirically validate the differences in the networks they generate on the Venetian Wikipedia with the real network of conversations extracted manually by coding every message left on all user talk pages. The comparisons show that both the algorithms and the manual process contain inaccuracies that are intrinsic in the freedom and unpredictability of Wikipedia growth. Nevertheless, a precise description of the involved issues allows to make informed decisions and to base empirical findings on reproducible evidence. Our goal is to lay the foundation for a solid computational sociology of wikis. For this reason we release the scripts encoding our algorithms as open source and also some datasets extracted out of Wikipedia conversations, in order to let other researchers replicate and improve our initial effort.||14||2|
|Web 2.0 in the professional LIS literature: An exploratory analysis||Noa Aharony||Journal of Librarianship and Information Science||English||2011||This paper presents a statistical descriptive analysis and a thorough content analysis of descriptors and journal titles extracted from the Library and Information Science Abstracts (LISA) database, focusing on the subject of Web 2.0 and its main applications: blog, wiki, social network and tags.The primary research questions include: whether the phenomenon of Web 2.0 with its various applications is significantly expressed in the professional LIS literature; which kind of journals deal with Web 2.0 and its applications; and what are the emerging issues or trends expressed in the professional LIS literature. The findings reveal that the percentage of peer-reviewed articles concerning Web 2.0 is quite low, and a close link between Web 2.0 and library issues. This tendency may suggest the potential of Web 2.0 and its implications for libraries, as presented in the professional LIS literature.||0||0|
|When the Wikipedians Talk: Network and Tree Structure of Wikipedia Discussion Pages||David Laniado
|ICWSM||English||2011||Talk pages play a fundamental role in Wikipedia as the place for discussion and communication. In this work we use the comments on these pages to extract and study three networks, corresponding to different kinds of interactions. We find evidence of a specific assortativity profile which differentiates article discussions from personal conversations. An analysis of the tree structure of the article talk pages allows to capture patterns of interaction, and reveals structural differences among the discussions about articles from different semantic areas.||0||2|
|A classification algorithm of signed networks based on link analysis||Qu Z.
|2010 International Conference on Communications, Circuits and Systems, ICCCAS 2010 - Proceedings||English||2010||In the signed networks the links between nodes can be either positive (means relations are friendship) or negative (means relations are rivalry or confrontation), which are very useful for analysis the real social network. After study data sets from Wikipedia and Slashdot networks, We find that the signs of links in the fundamental social networks can be used to classified the nodes and used to forecast the potential emerged sign of links in the future with high accuracy, using models that established across these diverse data sets. Based on the models, the proposed algorithm in the artwork provides perception into some of the underlying principles that extract from signed links in the networks. At the same time, the algorithm shed light on the social computing applications by which the attitude of a person toward another can be predicted from evidence provided by their around friends relationships.||0||0|
|Collective wisdom: Information growth in wikis and blogs||Sanmay Das
|Proceedings of the ACM Conference on Electronic Commerce||English||2010||Wikis and blogs have become enormously successful media for collaborative information creation. Articles and posts accrue information through the asynchronous editing of users who arrive both seeking information and possibly able to contribute information. Most articles stabilize to high quality, trusted sources of information representing the collective wisdom of all the users who edited the article. We propose a model for information growth which relies on two main observations: (i) as an article's quality improves, it attracts visitors at a faster rate (a rich get richer phenomenon); and, simultaneously, (ii) the chances that a new visitor will improve the article drops (there is only so much that can be said about a particular topic). Our model is able to reproduce many features of the edit dynamics observed on Wikipedia and on blogs collected from LiveJournal; in particular, it captures the observed rise in the edit rate, followed by 1/t decay.||0||0|
|Harnessing Collective Intelligence: Wiki and Social Network from End-user Perspective||Behnaz Gholami
|Harnessing collective intelligence: Wiki and social network from end-user perspective||Behnaz Gholami
|IC4E 2010 - 2010 International Conference on e-Education, e-Business, e-Management and e-Learning||English||2010||In the social web in which "people socialize or interact with each other throughout the World Wide Web, social interactions lead to the creation of explicit and meaningfully rich knowledge representations". Emergence of social web shed light on the concept of collective intelligence (CI). Web 2.0 technologies as key part of social semantic web, play an important role to harness the CI. Web 2.0 technologies are divided into the end-user and technical perspectives. In this paper CI and Web 2.0 is assessed with more details and through a theoretical framework regarding the end-user perspective. From all various kinds of Web 2.0 technologies Wikis and Social networks are chosen due to their huge contribution to CI. This paper focuses on end-user perspective of Wiki and Social network; categorizes the end-user perspective of these two technologies into 4 core aspects; and on the basis of findings from a web-based questionnaire, tests the relationship between each component of these 4 aspects and the CI.||0||0|
|Incorporating multi-partite networks and expertise to construct related-term graphs||Shieh J.-R.
|Proceedings - IEEE International Conference on Data Mining, ICDM||English||2010||Term suggestion techniques recommend query terms to a user based on his initial query. Providing adequate term suggestions is a challenging task. Most existing commercial search engines suggest search terms based on the frequency of prior used terms that match the first few letters typed by the user. We present a novel mechanism to construct semantic term-relation graphs to suggest semantically relevant search terms. We build term relation graphs based on multi-partite networks of existing social media. These linkage networks are extracted from Wikipedia to eventually form term relation graphs. We propose incorporating contributor-category networks to model the contributor expertise. This step has been shown to significantly enhance the accuracy of the inferred relatedness of the term-semantic graphs. Experiments showed the obvious advantage of our algorithms over existing approaches||0||0|
|Learning about team collaboration from Wikipedia edit history||Adam Wierzbicki
|Social network mining based on Improved Vector Space Model||Fangfang Yang
|Proceedings of the 2nd International Conference on Internet Multimedia Computing and Service, ICIMCS'10||English||2010||We employ a method to mine social networks of person entities from Wikipedia in this paper. A person entity is represented as a vector by anchor text set and content text set of his page in Wikipedia using Improved Vector Space Model (IVSM). We use cosine similarity of the vectors to present the similarity of person entities, and at last we get the similarity array of all the person entities. Finally, we extract the social network from the array which shows the relations of person entities. On Wikipedia data, we conduct some experiments on social network analysis, and the experimental results show our social network mining approaches are effective. Copyright 2010 ACM.||0||0|
|Social networking in academic libraries: The possibilities and the concerns||Dickson A.
|New Library World||English||2010||Purpose: The goal of this paper is to examine the use of the major social networking tools in academic libraries in the USA. As college students are heavy users of social networking, such efforts provide academic libraries with outreach possibilities to students who do not use the physical library. The paper also seeks to examine the concerns about their use both from students and within the academic library. Design/methodology/approach: The paper summarizes findings from articles published since 2006 found in the Library Literature and Information Full Text database. The first author also examined librarian blogs and library accounts in various social networking sites. Findings: Social networking can be an effective method of student outreach in academic libraries if libraries take care to respect student privacy and to provide equal coverage for all subject areas. Research limitations/implications: Most information about social networking is anecdotal with very little statistical analysis of its effectiveness. The popularity of the various social networking sites can change quickly. Practical implications: Academic libraries should consider using social networking as an outreach effort but take care to avoid the potential negative consequences. Originality/value: This paper provides a snapshot on the use of social networking in academic libraries through a thorough review of the available literature and an examination of the libraries' presence on the most popular social networking sites. It also provides help for academic libraries wishing to implement social networking.||0||0|
|What’s on Wikipedia and What’s Not... ?||Cindy Royal
|Social Science Computer Review||English||February 2009||The World Wide Web continues to grow closer to achieving the vision of becoming the repository of all human knowledge, as features and applications that support user-generated content become more prevalent. Wikipedia is fast becoming an important resource for news and information. It is an online information source that is increasingly used as the first, and sometimes only, stop for online encyclopedic information. Using a method employed by Tankard and Royal to judge completeness of Web content, completeness of information on Wikipedia is assessed. Some topics are covered more comprehensively than others, and the predictors of these biases include recency, importance, population, and financial wealth. Wikipedia is more a socially produced document than a value-free information source. It reflects the viewpoints, interests, and emphases of the people who use it.||6||1|
|ICT for health: Social computing||Cabrera M.
|Assistive Technology Research Series||English||2009||A question of extraordinary interest for the active ageing paradigm is the importance given to preventive medicine and the promotion of healthy lifestyles. In this sense, we consider that Social Computing is a very good example since its potential is enormous and needs to be further explored. It is obvious that ICT technologies, in general, facilitate the wider and quicker dissemination of healthy lifestyles and the prevention of dangerous habits. However, what is the added value offered by Web 2.0 applications, and how have Internet users' attitudes changed? And more specifically, what are the advantages for older citizens? Social computing: 1) facilitates the fast dissemination of preventive health measures and of healthy ways of living; 2) shortens the sometimes long wait for an appointment with a health professional; 3) facilitates the personalisation of health-related information making it more realistically accessible by posting reminders to patients of their periodic clinical examinations or seasonal vaccinations and 4) provides information adapted to the level of disability or the physical limitations. © 2009 The European Community and IOS Press. All rights reserved.||0||0|
|It's a network, not an encyclopedia: A social network perspective on Wikipedia collaboration||Kane G.C.||Academy of Management 2009 Annual Meeting: Green Management Matters, AOM 2009||English||2009||This paper studies the collaboration process on Wikipedia to determine whether particular collaborative processes are associated with article quality. Employing a sample of 300 articles on medical and health-related topics, this paper examines the impact of the article's position within the two-mode affiliation network of articles and editors on article quality. This paper finds that the position of the article within both the local and global networks of articles and editors is significantly related to article quality. These results suggest that editors transfer information and knowledge from one collaborative environment to another on the same platform. Somewhat surprisingly, the direct collaborative processes have little relationship to article quality. Taken together, these findings suggest that the social aspects of Wikipedia are indispensable for understanding its collaborative processes.||0||0|
|Metasocial wiki - Towards an interlinked knowledge in a decentralized social space||Cano A.E.
|CEUR Workshop Proceedings||English||2009||This paper introduces a new approach to semantic wikis. In this approach users coming from different social networks can be merged into a common space to enable collaboration. This approach makes use of the user's identity representation and keeping track of the user's interests according to the type of annotations encountered in the content they add.||0||0|
|Visualizing Intellectual Connections among Philosophers Using the Hyperlink & Semantic Data from Wikipedia||Sofia J. Athenikos
|Visualizing intellectual connections among philosophers using the hyperlink & semantic data from Wikipedia||Athenikos S.J.
|WikiSym||English||2009||Wikipedia, with its unique structural features and rich usergenerated content, is being increasingly recognized as a valuable knowledge source that can be exploited for various applications. The objective of the ongoing project reported in this paper is to create a Web-based knowledge portal for digital humanities based on the data extracted from Wikipedia (and other data sources). In this paper we present the interesting results we have obtained by extracting and visualizing various connections among 300 major philosophers using the structured data available in Wikipedia. Copyright||0||0|
|What's on Wikipedia, and What's Not . . . ?||Cindy Royal
|Soc. Sci. Comput. Rev.||English||2009||0||0|
|What's on wikipedia, and what's not... ?: Assessing completeness of information||Cindy Royal
|Social Science Computer Review||English||2009||The World Wide Web continues to grow closer to achieving the vision of becoming the repository of all human knowledge, as features and applications that support user-generated content become more prevalent. Wikipedia is fast becoming an important resource for news and information. It is an online information source that is increasingly used as the first, and sometimes only, stop for online encyclopedic information. Using a method employed by Tankard and Royal to judge completeness of Web content, completeness of information on Wikipedia is assessed. Some topics are covered more comprehensively than others, and the predictors of these biases include recency, importance, population, and financial wealth. Wikipedia is more a socially produced document than a value-free information source. It reflects the viewpoints, interests, and emphases of the people who use it.||0||0|
|Applying Web 2.0 design principles in the design of cooperative applications||Pinkwart N.||Lecture Notes in Computer Science||English||2008||"Web 2.0" is a term frequently mentioned in media - apparently, applications such as Wikipedia, Social Network Services, Online Shops with integrated recommender systems, or Sharing Services like flickr, all of which rely on user's activities, contributions, and interactions as a central factor, are fascinating for the general public. This leads to a success of these systems that seemingly exceeds the impact of most "traditional" groupware applications that have emerged from CSCW research. This paper discusses differences and similarities between novel Web 2.0 tools and more traditional CSCW application in terms of technologies, system design and success factors. Based on this analysis, the design of the cooperative learning application LARGO is presented to illustrate how Web 2.0 success factors can be considered for the design of cooperative environments.||0||0|
|Co-occurrence network of reuters news||Ozgur A.
|International Journal of Modern Physics C||English||2008||Networks describe various complex natural systems including social systems. We investigate the social network of co-occurrence in Reuters-21578 corpus, which consists of news articles that appeared in the Reuters newswire in 1987. People are represented as vertices and two persons are connected if they co-occur in the same article. The network has small-world features with power-law degree distribution. The network is disconnected and the component size distribution has power-law characteristics. Community detection on a degree-reduced network provides meaningful communities. An edge-reduced network, which contains only the strong ties has a star topology. "Importance" of persons are investigated. The network is the situation in 1987. After 20 years, a better judgment on the importance of the people can be done. A number of ranking algorithms, including Citation count and PageRank, are used to assign ranks to vertices. The ranks given by the algorithms are compared against how well a person is represented in Wikipedia. We find up to medium level Spearman's rank correlations. A noteworthy finding is that PageRank consistently performed worse than the other algorithms. We analyze this further and find reasons.||0||0|
|Extraction and analysis of tripartite relationships from Wikipedia||Nazir F.
|International Symposium on Technology and Society, Proceedings||English||2008||Social aspects are critical in the decision making process for social actors (human beings). Social aspects can be categorized into social interaction, social communities, social groups or any kind of behavior that emerges from interlinking, overlapping or similarities between interests of a society. These social aspects are dynamic and emergent. Therefore, interlinking them in a social structure, based on bipartite affiliation network, may result in isolated graphs. The major reason is that as these correspondences are dynamic and emergent, they should be coupled with more than a single affiliation in order to sustain the interconnections during interest evolutions. In this paper we propose to interlink actors using multiple tripartite graphs rather than a bipartite graph which was the focus of most of the previous social network building techniques. The utmost benefit of using tripartite graphs is that we can have multiple and hierarchical links between social actors. Therefore in this paper we discuss the extraction, plotting and analysis methods of tripartite relations between authors, articles and categories from Wikipedia. Furthermore, we also discuss the advantages of tripartite relationships over bipartite relationships. As a conclusion of this study we argue based on our results that to build useful, robust and dynamic social networks, actors should be interlinked in one or more tripartite networks.||0||1|
|Groups formation and operations in the web 2.0 environment and social networks||Lai L.S.L.
|Group Decision and Negotiation||English||2008||The Internet and the Web are evolving to a platform for collaboration, sharing, innovation and user-created content-the so-called Web 2.0 environment. This environment includes social and business networks, and it is influencing what people do on the Web and intranets, individually and in groups. This paper describes the Web 2.0 environment, its tools, applications, characteristics. It also describes various types of online groups, especially social networks, and how they operate in the Web 2.0 environment. Of special interest is the way organization members communicate and collaborate mainly via wikis and blogs. In addition, the paper includes a proposed triad relational model (Technology-People-Community) of social/work life on the Internet. Particularly, social/work groups are becoming sustainable because of the incentives for participants to connect and network with other users. A discussion of group dynamics that is based on the human needs for trust, support, and sharing, regardless if the setting is a physical or virtual one, follows. Finally, future research directions are outlined. © 2008 Springer Science+Business Media B.V.||0||0|
|Harnessisg social networks to connect with audiences: If you build it, will they come 2.0?||Belden D.||Internet Reference Services Quarterly||English||2008||Digital libraries offer users a wealth of online resources, but most of these materials remain hidden to potential users. Established strategies for outreach and promotion bring limited success when trying to connect with users accustomed to Googling their way through research. Social Networks provide an opportunity for connecting with audiences in the places they habitually seek information. The University of North Texas Libraries' Portal to Texas History (http://texashistory.unt.edu) has experienced dramatic increases in Web usage and reference requests by harnessing the power of social networks such as Wikipedia and MySpace.||0||0|
|Managing conflicts between users in Wikipedia||Jacquemin B.
|CEUR Workshop Proceedings||English||2008||Wikipedia is nowadays a widely used encyclopedia, and one of the most visible sites on the Internet. Its strong principle of collaborative work and free editing sometimes generates disputes due to disagreements between users. In this article we study how the wikipedian community resolves the conflicts and which roles do wikipedian choose in this process. We observed the users behavior both in the article talk pages, and in the Arbitration Committee pages specifically dedicated to serious disputes. We first set up a users typology according to their involvement in conflicts and their publishing and management activity in the encyclopedia. We then used those user types to describe users behavior in contributing to articles that are tagged by the wikipedian community as being in conflict with the official guidelines of Wikipedia, or conversely as being well featured.||0||0|
|On visualizing heterogeneous semantic networks from multiple data sources||Maureen
|Lecture Notes in Computer Science||English||2008||In this paper, we focus on the visualization of heterogeneous semantic networks obtained from multiple data sources. A semantic network comprising a set of entities and relationships is often used for representing knowledge derived from textual data or database records. Although the semantic networks created for the same domain at different data sources may cover a similar set of entities, these networks could also be very different because of naming conventions, coverage, view points, and other reasons. Since digital libraries often contain data from multiple sources, we propose a visualization tool to integrate and analyze the differences among multiple social networks. Through a case study on two terrorism-related semantic networks derived from Wikipedia and Terrorism Knowledge Base (TKB) respectively, the effectiveness of our proposed visualization tool is demonstrated.||0||0|
|WikiNetViz: Visualizing friends and adversaries in implicit social networks||Le M.-T.
|IEEE International Conference on Intelligence and Security Informatics, 2008, IEEE ISI 2008||English||2008||When multiple users with diverse backgrounds and beliefs edit Wikipedia together, disputes often arise due to disagreements among the users. In this paper, we introduce a novel visualization tool known as WikiNetViz to visualize and analyze disputes among users in a dispute-induced social network. WikiNetViz is designed to quantify the degree of dispute between a pair of users using the article history. Each user (and article) is also assigned a controversy score by our proposed ControversyRank model so as to measure the degree of controversy of a user (and an article) by the amount of disputes between the user (article) and other users in articles of varying degrees of controversy. On the constructed social network, WikiNetViz can perform clustering so as to visualize the dynamics of disputes at the user group level. It also provides an article viewer for examining an article revision so as to determine the article content modified by different users.||0||0|
|The Richness and Reach of Wikinomics: Is the Free Web-Based Encyclopedia Wikipedia Only for the Rich Countries?||Morten Rask||Proceedings of the Joint Conference of The International Society of Marketing Development and the Macromarketing Society, June 2-5, 2007||2007||In this paper, a model of the patterns of correlation in Wikipedia, reach and richness, lays the foundation for studying whether or not the free web-based encyclopedia Wikipedia is only for developed countries. Wikipedia is used in this paper, as an illustrative case study for the enormous rise of the so-called Web 2.0 applications, a subject which has become associated with many golden promises: Instead of being at the outskirts of the global economy, the development of free or low-cost internet-based content and applications, makes it possible for poor, emerging, and transition countries to compete and collaborate on the same level as developed countries. Based upon data from 12 different Wikipedia language editions, we find that the central structural effect is on the level of human development in the current country. In other words, Wikipedia is in general, more for rich countries than for less developed countries. It is suggested that policy makers make investments in increasing the general level of literacy, education, and standard of living in their country. The main managerial implication for businesses, that will expand their social network applications to other countries, is to use the model of the patterns of correlation in Wikipedia, reach and richness, as a market screening and monitoring model.||0||1|
|Viral knowledge acquisition through social networks||Soshnikov D.
|Lecture Notes in Computer Science||English||2007||In this paper, we present an approach for semi-structured knowledge acquisition through the concept of Structured Semantic Wiki, based on social virus spreading in the internet-based community. This approach allows harnessing collective intelligence of a community and inducing structured annotated knowledgebase of community relations by viral-driven actions of community participants.||0||0|
|Library 2.0 theory: Web 2.0 and its implications for libraries||Maness J.M.||Webology||English||2006||This article posits a definition and theory for "Library 2.0". It suggests that recent thinking describing the changing Web as "Web 2.0" will have substantial implications for libraries, and recognizes that while these implications keep very close to the history and mission of libraries, they still necessitate a new paradigm for librarianship. The paper applies the theory and definition to the practice of librarianship, specifically addressing how Web 2.0 technologies such as synchronous messaging and streaming media, blogs, wikis, social networks, tagging, RSS feeds, and mashups might intimate changes in how libraries provide access to their collections and user support for that access. Copyright © 2006, Jack M. Maness.||0||1|
|At the Crossroads of Knowledge Management with Social Software||Avram G.||Proceedings of the European Conference on Knowledge Management, ECKM||English||2005||The growing phenomenon of Social Software seems to provide a chance of complementing the top down approach based on central knowledge repositories with tools that are simpler, smarter and more flexible. Our paper includes a brief description of the main categories of Social Software - weblogs, wikis and social networking sites, followed by an analysis of their utilisation in relation to the five core Knowledge Management activities of the Knowledge Management taxonomy proposed by Despres & Chauvel in 1999. A couple of examples meant to illustrate the support Social Software could provide for knowledge management are presented. Finally, some of the problems that hinder the usage of social software tools, together with some of the latest developments and trends in the field are mentioned.||0||0|