Knowledge Quality of Collaborative Editing in Wikipedia: an Integrative Perspective of Social Capital and Team Conflict

Collaborative editing has become one of the most popular forms of knowledge contribution in virtual communities. Wikipedia— the largest online encyclopaedia— is a representative example of collaborative work. Despite the abundant researches on Wikipedia, to the best of our knowledge, no one has considered the integration of social capital and conflict. Besides, extant literatures on knowledge quality just pay attention to task conflict, while relational conflict is rarely mentioned. Meanwhile, our study proposes the nonlinear relationship between task conflict and knowledge quality instead of linear relationships in prior studies. We also postulate the moderating effect of task complexity. Furthermore, there is little empirical research on the influence of social capital on conflict, especially the distinct effects of cognitive and relational capital. This paper aims at proposing a theoretical model to examine the effect of social capital and conflict, meanwhile taking the task complexity into account. We will make our efforts to verify our research model in the following phases, and we believe that the present work can make some contributions to both research and practice

Conflict and Computation on Wikipedia: a Finite-State Machine Analysis of Editor Interactions

What is the boundary between a vigorous argument and a breakdown of relations? What drives a group of individuals across it? Taking Wikipedia as a test case, we use a hidden Markov model to approximate the computational structure and social grammar of more than a decade of cooperation and conflict among its editors. Across a wide range of pages, we discover a bursty war/peace structure where the systems can become trapped, sometimes for months, in a computational subspace associated with significantly higher levels of conflict-tracking "revert" actions. Distinct patterns of behavior characterize the lower-conflict subspace, including tit-for-tat reversion. While a fraction of the transitions between these subspaces are associated with top-down actions taken by administrators, the effects are weak. Surprisingly, we find no statistical signal that transitions are associated with the appearance of particularly anti-social users, and only weak association with significant news events outside the system. These findings are consistent with transitions being driven by decentralized processes with no clear locus of control. Models of belief revision in the presence of a common resource for information-sharing predict the existence of two distinct phases: a disordered high-conflict phase, and a frozen phase with spontaneously-broken symmetry. The bistability we observe empirically may be a consequence of editor turn-over, which drives the system to a critical point between them.Comment: 23 pages, 3 figures. Matches published version. Code for HMM fitting available at http://bit.ly/sfihmm ; time series and derived finite state machines at bit.ly/wiki_hm

Stigmergy in Web 2.0: a model for site dynamics

Building Web 2.0 sites does not necessarily ensure the success of the site. We aim to better understand what improves the success of a site by drawing insight from biologically inspired design patterns. Web 2.0 sites provide a mechanism for human interaction enabling powerful intercommunication between massive volumes of users. Early Web 2.0 site providers that were previously dominant are being succeeded by newer sites providing innovative social interaction mechanisms. Understanding what site traits contribute to this success drives research into Web sites mechanics using models to describe the associated social networking behaviour. Some of these models attempt to show how the volume of users provides a self-organising and self-contextualisation of content. One model describing coordinated environments is called stigmergy, a term originally describing coordinated insect behavior. This paper explores how exploiting stigmergy can provide a valuable mechanism for identifying and analysing online user behavior specifically when considering that user freedom of choice is restricted by the provided web site functionality. This will aid our building better collaborative Web sites improving the collaborative processes

Coordination and Efficiency in Decentralized Collaboration

Environments for decentralized on-line collaboration are now widespread on the Web, underpinning open-source efforts, knowledge creation sites including Wikipedia, and other experiments in joint production. When a distributed group works together in such a setting, the mechanisms they use for coordination can play an important role in the effectiveness of the group's performance. Here we consider the trade-offs inherent in coordination in these on-line settings, balancing the benefits to collaboration with the cost in effort that could be spent in other ways. We consider two diverse domains that each contain a wide range of collaborations taking place simultaneously -- Wikipedia and GitHub -- allowing us to study how coordination varies across different projects. We analyze trade-offs in coordination along two main dimensions, finding similar effects in both our domains of study: first we show that, in aggregate, high-status projects on these sites manage the coordination trade-off at a different level than typical projects; and second, we show that projects use a different balance of coordination when they are "crowded," with relatively small size but many participants. We also develop a stylized theoretical model for the cost-benefit trade-off inherent in coordination and show that it qualitatively matches the trade-offs we observe between crowdedness and coordination.Comment: 10 pages, 6 figures, ICWSM 2015, in Proc. 9th International AAAI Conference on Weblogs and Social Medi

Automatic detection of accommodation steps as an indicator of knowledge maturing

Jointly working on shared digital artifacts – such as wikis – is a well-tried method of developing knowledge collectively within a group or organization. Our assumption is that such knowledge maturing is an accommodation process that can be measured by taking the writing process itself into account. This paper describes the development of a tool that detects accommodation automatically with the help of machine learning algorithms. We applied a software framework for task detection to the automatic identification of accommodation processes within a wiki. To set up the learning algorithms and test its performance, we conducted an empirical study, in which participants had to contribute to a wiki and, at the same time, identify their own tasks. Two domain experts evaluated the participants’ micro-tasks with regard to accommodation. We then applied an ontology-based task detection approach that identified accommodation with a rate of 79.12%. The potential use of our tool for measuring knowledge maturing online is discussed

Education Unleashed: Participatory Culture, Education, and Innovation in Second Life

Part of the Volume on the Ecology of Games: Connecting Youth, Games, and LearningWhile virtual worlds share common technologies and audiences with games, they possess many unique characteristics. Particularly when compared to massively multiplayer online role-playing games, virtual worlds create very different learning and teaching opportunities through markets, creation, and connections to the real world, and lack of overt game goals. This chapter aims to expose a wide audience to the breadth and depth of learning occurring within Second Life (SL). From in-world classes in the scripting language to mixed-reality conferences about the future of broadcasting, a tremendous variety of both amateurs and experts are leveraging SL as a platform for education. In one sense, this isn't new since every technology is co-opted by communities for communication, but SL is different because every aspect of it was designed to encourage this co-opting, this remixing of the virtual and the real

Gender, power and emotions in the collaborative production of knowledge: A large-scale analysis of Wikipedia editor conversations

This paper studies the conversations behind the operations of a large-scale, online knowledge production community: Wikipedia. We investigate gender differences in the conversational styles (emotionality) and conversational domain choices (controversiality and gender stereotypicality of content) among contributors, and how these differences change as we look up the organizational hierarchy. In the general population of contributors, we expect and find significant gender differences, whereby comments and statements from women are higher-valenced, have more affective content, and are in domains that are less controversial and more female-typed. Importantly, these differences diminish or disappear among people in positions of power: female authorities converge to the behavior of their male counterparts, such that the gender gaps in valence and willingness to converse on controversial content disappear. We find greater sorting into topics according to their gender stereotypicality. We discuss mechanisms and implications for research on gender differences, leadership behavior, and conversational phenomena arising from such large-scale forms of knowledge production

Jointly they edit: examining the impact of community identification on political interaction in Wikipedia

In their 2005 study, Adamic and Glance coined the memorable phrase "divided they blog", referring to a trend of cyberbalkanization in the political blogosphere, with liberal and conservative blogs tending to link to other blogs with a similar political slant, and not to one another. As political discussion and activity increasingly moves online, the power of framing political discourses is shifting from mass media to social media. Continued examination of political interactions online is critical, and we extend this line of research by examining the activities of political users within the Wikipedia community. First, we examined how users in Wikipedia choose to display (or not to display) their political affiliation. Next, we more closely examined the patterns of cross-party interaction and community participation among those users proclaiming a political affiliation. In contrast to previous analyses of other social media, we did not find strong trends indicating a preference to interact with members of the same political party within the Wikipedia community. Our results indicate that users who proclaim their political affiliation within the community tend to proclaim their identity as a "Wikipedian" even more loudly. It seems that the shared identity of "being Wikipedian" may be strong enough to triumph over other potentially divisive facets of personal identity, such as political affiliation.Comment: 33 pages, 5 figure