Bongwon Suh

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Bongwon Suh is an author.

Publications

Only those publications related to wikis are shown here.
Title Keyword(s) Published in Language DateThis property is a special property in this wiki. Abstract R C
Invasion biology and the success of social collaboration networks, with application to wikipedia Invasion biology
Social collaboration networks
Stochastic population theory
Wikipedia
Israel Journal of Ecology and Evolution English 2013 We adapt methods from the stochastic theory of invasions - for which a key question is whether a propagule will grow to an established population or fail - To show how monitoring early participation in a social collaboration network allows prediction of success. Social collaboration networks have become ubiquitous and can now be found in widely diverse situations. However, there are currently no methods to predict whether a social collaboration network will succeed or not, where success is defined as growing to a specified number of active participants before falling to zero active participants. We illustrate a suitable methodology with Wikipedia. In general, wikis are web-based software that allows collaborative efforts in which all viewers of a page can edit its contents online, thus encouraging cooperative efforts on text and hypertext. The English language Wikipedia is one of the most spectacular successes, but not all wikis succeed and there have been some major failures. Using these new methods, we derive detailed predictions for the English language Wikipedia and in summary for more than 250 other language Wikipedias. We thus show how ideas from population biology can inform aspects of technology in new and insightful ways. 0 0
A comparison of generated Wikipedia profiles using social labeling and automatic keyword extraction ICWSM 2010 - Proceedings of the 4th International AAAI Conference on Weblogs and Social Media English 2010 In many collaborative systems, researchers are interested in creating representative user profiles. In this paper, we are particularly interested in using social labeling and automatic keyword extraction techniques for generating user profiles. Social labeling is a process in which users manually tag other users with keywords. Automatic keyword extraction is a technique that selects the most salient words to represent a user's contribution. We apply each of these two profile generation methods to highly active Wikipedia editors and their contributions, and compare the results. We found that profiles generated through social labeling matches the profiles generated via automatic keyword extraction, and vice versa. The results suggest that user profiles generated from one method can be used as a seed or bootstrapping proxy for the other method. Copyright © 2010, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved. 0 0
So you know you're getting the best possible information: A tool that increases wikipedia credibility Credibility
Wikidashboard
Wikipedia
Conference on Human Factors in Computing Systems - Proceedings English 2009 An experiment was conducted to study how credibility judgments about Wikipedia are affected by providing users with an interactive visualization (WikiDashboard) of article and author editing history. Overall, users who self-reported higher use of Internet information and higher rates of Wikipedia usage tended to produce lower credibility judgments about Wikipedia articles and authors. However, use of WikiDashboard significantly increased article and author credibility judgments, with effect sizes larger than any other measured effects of background media usage and attitudes on Wikiepedia credibility. The results suggest that increased exposure to the editing/authoring histories of Wikipedia increases credibility judgments. Copyright 2009 ACM. 0 0
So you know you're getting the best possible information: a tool that increases Wikipedia credibility Wikidashboard
Wikipedia
Credibility
Conference on Human Factors in Computing Systems English 2009 An experiment was conducted to study how credibility judgments about Wikipedia are affected by providing users with an interactive visualization (WikiDashboard) of article and author editing history. Overall, users who self-reported higher use of Internet information and higher rates of Wikipedia usage tended to produce lower credibility judgments about Wikipedia articles and authors. However, use of WikiDashboard significantly increased article and author credibility judgments, with effect sizes larger than any other measured effects of background media usage and attitudes on Wikiepedia credibility. The results suggest that increased exposure to the editing/authoring histories of Wikipedia increases credibility judgments. 0 0
The singularity is not near: slowing growth of Wikipedia Growth
Logistic model
Population
Power law
Resistance
Wikipedia
WikiSym English 2009 Prior research on Wikipedia has characterized the growth in content and editors as being fundamentally exponential in nature, extrapolating current trends into the future. We show that recent editing activity suggests that Wikipedia growth has slowed, and perhaps plateaued, indicating that it may have come against its limits to growth. We measure growth, population shifts, and patterns of editor and administrator activities, contrasting these against past results where possible. Both the rate of page growth and editor growth has declined. As growth has declined, there are indicators of increased coordination and overhead costs, exclusion of newcomers, and resistance to new edits. We discuss some possible explanations for these new developments in Wikipedia including decreased opportunities for sharing existing knowledge and increased bureaucratic stress on the socio-technical system itself. 0 13
What's in Wikipedia?: mapping topics and conflict using socially annotated category structure Wikipedia
Annotation
Conflict
Distributed collaboration
Mapping
Social computing
Visualisation
Wiki
Conference on Human Factors in Computing Systems English 2009 0 1
What's in wikipedia? Mapping topics and conflict using socially annotated category structure Annotation
Conflict
Distributed collaboration
Mapping
Social computing
Visualisation
Wiki
Wikipedia
Conference on Human Factors in Computing Systems - Proceedings English 2009 Wikipedia is an online encyclopedia which has undergone tremendous growth. However, this same growth has made it difficult to characterize its content and coverage. In this paper we develop measures to map Wikipedia using its socially annotated, hierarchical category structure. We introduce a mapping technique that takes advantage of socially-annotated hierarchical categories while dealing with the inconsistencies and noise inherent in the distributed way that they are generated. The technique is demonstrated through two applications: mapping the distribution of topics in Wikipedia and how they have changed over time; and mapping the degree of conflict found in each topic area. We also discuss the utility of the approach for other applications and datasets involving collaboratively annotated category hierarchies. Copyright 2009 ACM. 0 1
What’s in Wikipedia? Mapping Topics and Conflict Using Socially Annotated Category Structure English 2009 0 0
Augmented Social Cognition AAAI Spring Symposium - Technical Report English 2008 Research in Augmented Social Cognition is aimed at enhancing the ability of a group of people to remember, think, and reason; to augment their speed and capacity to acquire, produce, communicate, and use knowledge; and to advance collective and individual intelligence in socially mediated information environments. In this paper, we describe the emergence of this research endeavor, and summarize some results from the research. In particular, we have found that (1) analyses of conflicts and coordination in Wikipedia have shown us the scientific need to understand social sensemaking environments; and (2) information theoretic analyses of social tagging behavior in del.icio.us shows the need to understand human vocabulary systems. 0 0
Can you ever trust a wiki? Impacting perceived trustworthiness in wikipedia Collaboration
Social computing
Stability
Trust
Visualisation
Wiki
Wikipedia
English 2008 Wikipedia has become one of the most important information resources on the Web by promoting peer collaboration and enabling virtually anyone to edit anything. However, this mutability also leads many to distrust it as a reliable source of information. Although there have been many attempts at developing metrics to help users judge the trustworthiness of content, it is unknown how much impact such measures can have on a system that is perceived as inherently unstable. Here we examine whether a visualization that exposes hidden article information can impact readers' perceptions of trustworthiness in a wiki environment. Our results suggest that surfacing information relevant to the stability of the article and the patterns of editor behavior can have a significant impact on users' trust across a variety of page types. Copyright 2008 ACM. 0 0
Crowdsourcing user studies with Mechanical Turk Mechanical Turk
Micro task
Remote user study
Wikipedia
Conference on Human Factors in Computing Systems - Proceedings English 2008 User studies are important for many aspects of the design process and involve techniques ranging from informal surveys to rigorous laboratory studies. However, the costs involved in engaging users often requires practitioners to trade off between sample size, time requirements, and monetary costs. Micro-task markets, such as Amazon's Mechanical Turk, offer a potential paradigm for engaging a large number of users for low time and monetary costs. Here we investigate the utility of a micro-task market for collecting user measurements, and discuss design considerations for developing remote micro user evaluation tasks. Although micro-task markets have great potential for rapidly collecting user measurements at low costs, we found that special care is needed in formulating tasks in order to harness the capabilities of the approach. Copyright 2008 ACM. 0 0
Lifting the veil: Improving accountability and social transparency in Wikipedia with WikiDashboard Accountability
Collaboration
Social transparency
Trust
Visualisation
Wiki
Wikidashboard
Wikipedia
Conference on Human Factors in Computing Systems - Proceedings English 2008 Wikis are collaborative systems in which virtually anyone can edit anything. Although wikis have become highly popular in many domains, their mutable nature often leads them to be distrusted as a reliable source of information. Here we describe a social dynamic analysis tool called WikiDashboard which aims to improve social transparency and accountability on Wikipedia articles. Early reactions from users suggest that the increased transparency afforded by the tool can improve the interpretation, communication, and trustworthiness of Wikipedia articles. Copyright 2008 ACM. 0 4
Lifting the veil: improving accountability and social transparency in Wikipedia with wikidashboard English 2008 Wikis are collaborative systems in which virtually anyone can edit anything. Although wikis have become highly popular in many domains, their mutable nature often leads them to be distrusted as a reliable source of information. Here we describe a social dynamic analysis tool called WikiDashboard which aims to improve social transparency and accountability on Wikipedia articles. Early reactions from users suggest that the increased transparency afforded by the tool can improve the interpretation, communication, and trustworthiness of Wikipedia articles. 0 4
He says, she says: conflict and coordination in Wikipedia English 2007 Wikipedia, a wiki-based encyclopedia, has become one of the most successful experiments in collaborative knowledge building on the Internet. As Wikipedia continues to grow, the potential for conflict and the need for coordination increase as well. This article examines the growth of such non-direct work and describes the development of tools to characterize conflict and coordination costs in Wikipedia. The results may inform the design of new collaborative knowledge systems. 0 20
Us vs. Them: Understanding Social Dynamics in Wikipedia with Revert Graph Visualizations Visual Analytics Science and Technology English 2007 Wikipedia is a wiki-based encyclopedia that has become one of the most popular collaborative on-line knowledge systems. As in any large collaborative system, as Wikipedia has grown, conflicts and coordination costs have increased dramatically. Visual analytic tools provide a mechanism for addressing these issues by enabling users to more quickly and effectively make sense of the status of a collaborative environment. In this paper we describe a model for identifying patterns of conflicts in Wikipedia articles. The model relies on users' editing history and the relationships between user edits, especially revisions that void previous edits, known as "reverts". Based on this model, we constructed Revert Graph, a tool that visualizes the overall conflict patterns between groups of users. It enables visual analysis of opinion groups and rapid interactive exploration of those relationships via detail drill- downs. We present user patterns and case studies that show the effectiveness of these techniques, and discuss how they could generalize to other systems. 0 4
Us vs. Them: Understanding social dynamics in wikipedia with revert graph visualizations Collaboration
Graph
Revert
User model
Visualisation
Wiki
Wikipedia
VAST IEEE Symposium on Visual Analytics Science and Technology 2007, Proceedings English 2007 Wikipedia is a wiki-based encyclopedia that has become one of the most popular collaborative on-line knowledge systems. As in any large collaborative system, as Wikipedia has grown, conflicts and coordination costs have increased dramatically. Visual analytic tools provide a mechanism for addressing these issues by enabling users to more quickly and effectively make sense of the status of a collaborative environment. In this paper we describe a model for identifying patterns of conflicts in Wikipedia articles. The model relies on users' editing history and the relationships between user edits, especially revisions that void previous edits, known as "reverts". Based on this model, we constructed Revert Graph, a tool that visualizes the overall conflict patterns between groups of users. It enables visual analysis of opinion groups and rapid interactive exploration of those relationships via detail drill-downs. We present user patterns and case studies that show the effectiveness of these techniques, and discuss how they could generalize to other systems. 0 4