Darren Gergle

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Darren Gergle is an author from United States.

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
Hot Off the Wiki: Structures and Dynamics of Wikipedia's Coverage of Breaking News Events Collaboration
News
Social network
Wikipedia
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
Staying in the Loop: Structure and Dynamics of Wikipedia's Breaking News Collaborations Wikipedia
High-tempo collaboration
Network analysis
Breaking news
Collaboration
Multigraph
WikiSym English August 2012 Despite the fact that Wikipedia articles about current events are more popular and attract more contributions than typical articles, canonical studies of Wikipedia have only analyzed articles about pre-existing information. We expect the co-authoring of articles about breaking news incidents to exhibit high-tempo coordination dynamics which are not found in articles about historical events and information. Using 1.03 million revisions made by 158,384 users to 3,233 English Wikipedia articles about disasters, catastrophes, and conflicts since 1990, we construct “article trajectories” of editor interactions as they coauthor an article. Examining a subset of this corpus, our analysis demonstrates that articles about current events exhibit structures and dynamics distinct from those observed among articles about non-breaking events. These findings have implications for how collective intelligence systems can be leveraged to process and make sense of complex information. 0 0
Do editors or articles drive collaboration? Multilevel statistical network analysis of wikipedia coauthorship Co-authorship
Collaboration
Ergm
Exponential random graph model
Network analysis
Socio-material
Wikipedia
English 2012 Prior scholarship on Wikipedia's collaboration processes has examined the properties of either editors or articles, but not the interactions between both. We analyze the coauthorship network of Wikipedia articles about breaking news demanding intense coordination and compare the properties of these articles and the editors who contribute to them to articles about contemporary and historical events. Using p*/ERGM methods to test a multi-level, multi-theoretical model, we identify how editors' attributes and editing patterns interact with articles' attributes and authorship history. Editors' attributes like prior experience have a stronger influence on collaboration patterns, but article attributes also play significant roles. Finally, we discuss the implications our findings and methods have for understanding the socio-material duality of collective intelligence systems beyond Wikipedia. 0 1
Explanatory semantic relatedness and explicit spatialization for exploratory search Cartography
Exploratory search
Geography
Giscience
Semantic relatedness
Spatialization
Text mining
Wikipedia
SIGIR'12 - Proceedings of the International ACM SIGIR Conference on Research and Development in Information Retrieval English 2012 Exploratory search, in which a user investigates complex concepts, is cumbersome with today's search engines. We present a new exploratory search approach that generates interactive visualizations of query concepts using thematic cartography (e.g. choropleth maps, heat maps). We show how the approach can be applied broadly across both geographic and non-geographic contexts through explicit spatialization, a novel method that leverages any figure or diagram - from a periodic table, to a parliamentary seating chart, to a world map - as a spatial search environment. We enable this capability by introducing explanatory semantic relatedness measures. These measures extend frequently-used semantic relatedness measures to not only estimate the degree of relatedness between two concepts, but also generate human-readable explanations for their estimates by mining Wikipedia's text, hyperlinks, and category structure. We implement our approach in a system called Atlasify, evaluate its key components, and present several use cases. 0 0
Omnipedia: Bridging the Wikipedia Language Gap Wikipedia
Hyperlingual
Language barrier
User generated content
Text mining
International Conference on Human Factors in Computing Systems English 2012 We present Omnipedia, a system that allows Wikipedia readers to gain insight from up to 25 language editions ofWikipedia simultaneously. Omnipedia highlights the similarities and differences that exist among Wikipedia language editions, and makes salient information that is unique to each language as well as that which is shared more widely. We detail solutions to numerous front-end and algorithmic challenges inherent to providing users with a multilingual Wikipedia experience. These include visualizing content in a language-neutral way and aligning data in the face of diverse information organization strategies. We present a study of Omnipedia that characterizes how people interact with information using a multilingual lens. We found that users actively sought information exclusive to unfamiliar language editions and strategically compared how language editions defined concepts. Finally, we briefly discuss how Omnipedia generalizes to other domains facing language barriers. 0 0
Omnipedia: Bridging the Wikipedia language gap Hyperlingual
Language barrier
Text mining
User generated content
Wikipedia
Conference on Human Factors in Computing Systems - Proceedings English 2012 We present Omnipedia, a system that allows Wikipedia readers to gain insight from up to 25 language editions of Wikipedia simultaneously. Omnipedia highlights the similarities and differences that exist among Wikipedia language editions, and makes salient information that is unique to each language as well as that which is shared more widely. We detail solutions to numerous front-end and algorithmic challenges inherent to providing users with a multilingual Wikipedia experience. These include visualizing content in a language-neutral way and aligning data in the face of diverse information organization strategies. We present a study of Omnipedia that characterizes how people interact with information using a multilingual lens. We found that users actively sought information exclusive to unfamiliar language editions and strategically compared how language editions defined concepts. Finally, we briefly discuss how Omnipedia generalizes to other domains facing language barriers. Copyright 2012 ACM. 0 0
Staying in the loop: Structure and dynamics of Wikipedia's breaking news collaborations Breaking news
Collaboration
High-tempo collaboration
Multigraph
Network analysis
Wikipedia
WikiSym 2012 English 2012 Despite the fact that Wikipedia articles about current events are more popular and attract more contributions than typical articles, canonical studies of Wikipedia have only analyzed articles about pre-existing information. We expect the co-authoring of articles about breaking news incidents to exhibit high-tempo coordination dynamics which are not found in articles about historical events and information. Using 1.03 million revisions made by 158,384 users to 3,233 English Wikipedia articles about disasters, catastrophes, and conflicts since 1990, we construct "article trajectories" of editor interactions as they coauthor an article. Examining a subset of this corpus, our analysis demonstrates that articles about current events exhibit structures and dynamics distinct from those observed among articles about non-breaking events. These findings have implications for how collective intelligence systems can be leveraged to process and make sense of complex information. 0 0
Hot off the Wiki: Dynamics, Practices, and Structures in Wikipedia’s Coverage of the Tōhoku Catastrophes Wikipedia
Breaking news
Current events
Network analysis
Bipartite network
Emergent group
High tempo
Collaboration
WikiSym English 2011 Wikipedia editors are uniquely motivated to collaborate around current and breaking news events. However, the speed, urgency, and intensity with which these collaborations unfold also impose a substantial burden on editors’ abilities to effectively coordinate tasks and process information. We analyze the patterns of activity on Wikipedia following the 2011 Tōhoku earthquake and tsunami to understand the dynamics of editor attention and participation, novel practices employed to collaborate on these articles, and the resulting coauthorship structures which emerge between editors and articles. Our findings have implications for supporting future coverage of breaking news articles, theorizing about motivations to participate in online community, and illuminating Wikipedia’s potential role in storing cultural memories of catastrophe. 0 0
Egalitarians at the gate: One-sided gatekeeping practices in social media Collaboration
Decision-making
Deliberation
Gatekeeping
Social computing
Wiki
Wikipedia
English 2010 Although Wikipedia has increasingly attracted attention for its in-depth and timely coverage of breaking news stories, the social dynamics of how Wikipedia editors process breaking news items has not been systematically examined. Through a 3-month study of 161 deliberations over whether a news item should appear on Wikipedia's front page, we demonstrate that elite users fulfill a unique gatekeeping role that permits them to leverage their community position to block the promotion of inappropriate items. However, these elite users are unable to promote their supported news items more effectively than other types of editors. These findings suggest that "one-sided gatekeeping" may reflect a crucial stasis in social media where the community has to balance the experience of its elite users while encouraging contributions from non-elite users. Copyright 2010 ACM. 0 1
On the "localness" of user-generated content Flickr
Local
User behavior
User generated content
Volunteered geographic information
Wikipedia
English 2010 The "localness" of participation in repositories of user-generated content (UGC) with geospatial components has been cited as one of UGC's greatest benefits. However, the degree of localness in major UGC repositories such as Flickr and Wikipedia has never been examined. We show that over 50 percent of Flickr users contribute local information on average, and over 45 percent of Flickr photos are local to the photographer. Across four language editions of Wikipedia, however, we find that participation is less local. We introduce the spatial content production model (SCPM) as a possible factor in the localness of UGC, and discuss other theoretical and applied implications. Copyright 2010 ACM. 0 0
The Tower of Babel Meets Web 2.0: User-Generated Content and Its Applications in a Multilingual Context International Conference on Human Factors in Computing Systems English 2010 This study explores language's fragmenting effect on user-generated content by examining the diversity of knowledge representations across 25 different Wikipedia language editions. This diversity is measured at two levels: the concepts that are included in each edition and the ways in which these concepts are described. We demonstrate that the diversity present is greater than has been presumed in the literature and has a significant influence on applications that use Wikipedia as a source of world knowledge. We close by explicating how knowledge diversity can be beneficially leveraged to create "culturally-aware applications" and "hyperlingual applications". 0 2
The tower of Babel meets web 2.0: User-generated content and its applications in a multilingual context Explicit semantic analysis
Hyperlingual
Knowledge diversity
Language
Semantic relatedness
Wikipedia
Conference on Human Factors in Computing Systems - Proceedings English 2010 This study explores language's fragmenting effect on user-generated content by examining the diversity of knowledge representations across 25 different Wikipedia language editions. This diversity is measured at two levels: the concepts that are included in each edition and the ways in which these concepts are described. We demonstrate that the diversity present is greater than has been presumed in the literature and has a significant influence on applications that use Wikipedia as a source of world knowledge. We close by explicating how knowledge diversity can be beneficially leveraged to create "culturally- aware applications" and "hyperlingual applications". 0 2
Measuring Self-Focus Bias in Community-Maintained Knowledge Repositories International Conference on Communities and Technologies English 2009 Self-focus is a novel way of understanding a type of bias in community-maintained Web 2.0 graph structures. It goes beyond previous measures of topical coverage bias by encapsulating both node- and edge-hosted biases in a single holistic measure of an entire community-maintained graph. We outline two methods to quantify self-focus, one of which is very computationally inexpensive, and present empirical evidence for the existence of self-focus using a "hyperlingual" approach that examines 15 different language editions of Wikipedia. We suggest applications of our methods and discuss the risks of ignoring self-focus bias in technological applications. 0 0