Dan Cosley
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| Dan Cosley (Alternative names for this author) | |
| Affiliation | Unknown [+] |
| Country | Unknown [+] |
| Co-authors | Austin Lin, Dan Frankowski, Fedor Dokshin, Geri Gay, Gueorgi Kossinets, Howard T. Welser, Jocelyn M. DeGroot, John Riedl, Laura W. Black, Loren Terveen, Marc Smith |
| Website | Unknown [+] |
| Statistics | |
| Authorship | Publications (3), datasets (0), tools (0) |
| Citations | Total (4), average (1.33333333333), median (0), max (4), min (0) |
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Dan Cosley 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 |
|---|---|---|---|---|---|---|---|
| Finding social roles in Wikipedia | English | 2011 | This paper investigates some of the social roles people play in the online community of Wikipedia. We start from qualitative comments posted on community oriented pages, wiki project memberships, and user talk pages in order to identify a sample of editors who represent four key roles: substantive experts, technical editors, vandal fighters, and social networkers. Patterns in edit histories and egocentric network visualizations suggest potential "structural signatures" that could be used as quantitative indicators of role adoption. Using simple metrics based on edit histories we compare two samples of Wikipedians: a collection of long term dedicated editors, and a cohort of editors from a one month window of new arrivals. According to these metrics, we find that the proportions of editor types in the new cohort are similar those observed in the sample of dedicated contributors. The number of new editors playing helpful roles in a single month's cohort nearly equal the number found in the dedicated sample. This suggests that informal socialization has the potential provide sufficient role related labor despite growth and change in Wikipedia. These results are preliminary, and we describe several ways that the method can be improved, including the expansion and refinement of role signatures and identification of other important social roles. | 0 | 4 | ||
| Self-Governance Through Group Discussion in Wikipedia: Measuring Deliberation in Online Groups | Small Group Research | English | 2011 | Virtual teams and other online groups can find it challenging to establish norms that allow them to effectively balance task and relational aspects of their discussions. Yet, in our reliance on organizational and team theories, small group scholars have overlooked the potential for learning from examples offered by online communities.Theories of deliberation in small groups offer scholars a way to assess such discussion-centered self-governance in online groups.The study operationalizes the conceptual definition of deliberative discussion offered by Gastil and Black (2008) to examine the small group discussions that undergird policy-making processes in a well-established online community, Wikipedia. Content analysis shows that these discussions demonstrated a relatively high level of problem analysis and providing of information, but results were mixed in the group’s demonstration of respect, consideration, and mutual comprehension. Network visualizations reveal structural patterns that can be useful in examining equality, influence, and group member roles. The combination of measures has implications for future research in deliberative discussion and virtual teamwork. | 0 | 0 | |
| SuggestBot: using intelligent task routing to help people find work in Wikipedia | Online community Member-maintained communities Wikipedia Intelligent task routing Recommender system |
English | 2007 | Member-maintained communities ask their users to perform tasks the community needs. From Slashdot, to IMDb, to Wikipedia, groups with diverse interests create community-maintained artifacts of lasting value (CALV) that support the group's main purpose and provide value to others. Said communities don't help members find work to do, or do so without regard to individual preferences, such as Slashdot assigning meta-moderation randomly. Yet social science theory suggests that reducing the cost and increasing the personal value of contribution would motivate members to participate more. We present SuggestBot, software that performs intelligent task routing (matching people with tasks) in Wikipedia. SuggestBot uses broadly applicable strategies of text analysis, collaborative filtering, and hyperlink following to recommend tasks. SuggestBot's intelligent task routing increases the number of edits by roughly four times compared to suggesting random articles. Our contributions are: 1) demonstrating the value of intelligent task routing in a real deployment; 2) showing how to do intelligent task routing; and 3) sharing our experience of deploying a tool in Wikipedia, which offered both challenges and opportunities for research. | 0 | 0 |
