Personal communication networks and their positive effects on online collaboration and outcome quality on <scp>W</scp>ikipedia

Tsikerdekis, Michail

doi:10.1002/asi.23429

Cited by 3 publications

(7 citation statements)

References 33 publications

(31 reference statements)

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“…Besides traditional face‐to‐face groups, virtual groups, for example, Group Decision Support Systems (GDSS) and computer‐mediated communication (CMC) groups, enabled by information and communication technologies (ICT), are increasingly used by organizations (Barlow & Dennis, ). Given the importance of the quality of decisions produced by GDSS or CMC groups, crowd performance has been widely investigated in GDSS (Tsikerdekis, ) and CMC groups (Barlow & Dennis, ). After conducting a meta‐analysis, Dennis and Wixom () found task type, Group Support Systems (GSS) tools type, group type, group size, and facilitation are important factors influencing GSS performance.…”

Section: Related Workmentioning

confidence: 99%

Crowd characteristics and crowd wisdom: Evidence from an online investment community

Hong

et al. 2019

Asso for Info Science & Tech

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Fueled by the explosive growth of Web 2.0 and social media, online investment communities have become a popular venue for individual investors to interact with each other. Investor opinions extracted from online investment communities capture “crowd wisdom” and have begun to play an important role in financial markets. Existing research confirms the importance of crowd wisdom in stock predictions, but fails to investigate factors influencing crowd performance (that is, crowd prediction accuracy). In order to help improve crowd performance, our research strives to investigate the impact of crowd characteristics on crowd performance. We conduct an empirical study using a large data set collected from a popular online investment community, StockTwits. Our findings show that experience diversity, participant independence, and network decentralization are all positively related to crowd performance. Furthermore, crowd size moderates the influence of crowd characteristics on crowd performance. From a theoretical perspective, our work enriches extant literature by empirically testing the relationship between crowd characteristics and crowd performance. From a practical perspective, our findings help investors better evaluate social sensors embedded in user‐generated stock predictions, based upon which they can make better investment decisions.

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Section: Related Workmentioning

confidence: 99%

Crowd characteristics and crowd wisdom: Evidence from an online investment community

Hong

et al. 2019

Asso for Info Science & Tech

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“…The latter is found to be the responsibility of a minority of users (Arazy & Nov, 2010;Halfaker, Geiger, Morgan, & Riedl, 2013;Kittur & Kraut, 2008). This minority of users have also been found to implicitly mentor inexperienced users (Tsikerdekis, 2016). Openstreetmaps, another collaborative project not in the wiki family, has been found to exhibit the same collaboration patterns.…”

Section: Collaborative Project Sizementioning

confidence: 88%

“…Projects include user bases that are small (Fulk & Steinfield, 1990;J. Nunamaker et al, 1989) and extend to large communities with millions of users (Kaplan & Haenlein, 2014;Mesgari et al, 2015;Tsikerdekis, 2016). Small groups have been found to provide more satisfying experiences (Fulk & Steinfield, 1990).…”

Section: Collaborative Project Sizementioning

confidence: 99%

Designing a Successful Collaborative Wiki

Tsikerdekis

2017

International Journal of Technology and Human Interaction

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Designing a collaborative platform that produces project outcomes of high quality and allows for wisdom of the crowds to come together in the achievement of a common goal can be a challenge. Literature often addresses the interplay between designing for online community needs and outcome/product quality as coexistence, where design implementations in one positively affect the other. However, Human-Computer Interaction research has shown that performance and satisfaction need not be dependent on each other. This paper performs a theoretical analysis of the literature on the topic and identifies design gaps for collaborative projects. Findings derived by this theoretical analysis challenge existing design perspectives by demonstrating that there is often a tradeoff between designing for online community needs and outcome quality for these projects. Claims were developed that lead to research questions identifying the most important elements and design considerations are provided along with potential future directions for advancing the understanding of this relationship.

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“…The English branch of Wikipedia at the time of the study had 4,903,920 articles, some of which have quality ratings received by Wikiprojects ("Special:Statistics," 2015). Studies on Wikipedia have shown that most articles on Wikipedia belong to the lower level categories, while a few thousand make it to the top categories (Kittur & Kraut, 2008;Tsikerdekis, 2016).…”

Section: Quality Assessment Classes In Wikipediamentioning

confidence: 99%

“…The overall experience (or reputation of editors, as it was called) in an article was measured in various forms based on the total revisions on an article, or limited to just the first few revisions ever made on an article. The selection of the particular namespaces, as opposed to others, was made based on past literature suggesting that Wikipedia's personal communication networks (in user talk pages) have an impact on quality (Tsikerdekis, 2016) and that some users are better integrated with community activities (by assuming different roles) (Welser et al, 2011), which could potentially impact quality. The latter was obtained through a proxy, which was participation on Wikipedia's policy pages.…”

Section: Cumulative Experience In Wikipedia and Wikipedia Talk Namespmentioning

confidence: 99%

Cumulative Experience and Recent Behavior and their Relation to Content Quality on Wikipedia

Tsikerdekis

2017

Interacting With Computers

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Research highlights Recent behavior a more powerful predictor than cumulative experience as a user characteristic that impact on content quality  Recent behavior in editing high quality articles impact content quality  Integrated users in the community have a higher impact on content quality ABSTRACTCumulative experience is often seen as a major factor for influencing content quality in collaborative projects such as Wikipedia. However, past studies often utilize cumulative experience based on the quantity of work rather than quality and context. Moreover, the perspective on cumulative experience assumes a final destination for user behavior, whereas much of the literature indicates that user behavior changes over time. This paper aims to address these two factors by providing better descriptions and context to determine their effect on content quality. The study rematerialized these factors based on Cumulative experience and recent behavior and their relation to content quality on WikipediaResearch highlights  Recent behavior is a more powerful predictor than cumulative experience as a user characteristic that impacts content quality  Recent behavior in editing high quality articles impacts content quality  Integrated users in the community have a higher impact on content quality ABSTRACTCumulative experience is often seen as a major factor for influencing content quality in collaborative projects such as Wikipedia. However, past studies often utilize cumulative experience based on the quantity of work rather than quality and context. Moreover, the perspective on cumulative experience assumes a final destination for user behavior, whereas much of the literature indicates that user behavior changes over time. This paper aims to address these two factors by providing better descriptions and context to determine their effect on content quality. The study rematerialized these factors based on the quality of work and built a comprehensive model of how article quality materializes through groups of users. Regression models in this study indicate that recent behavior is a more powerful predictor of content quality change than cumulative experience. The implications of the findings impact the design of task-routing systems as well as designers and group managers' work in collaborative projects.

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Personal communication networks and their positive effects on online collaboration and outcome quality on Wikipedia

Cited by 3 publications

References 33 publications

Crowd characteristics and crowd wisdom: Evidence from an online investment community

Crowd characteristics and crowd wisdom: Evidence from an online investment community

Designing a Successful Collaborative Wiki

Cumulative Experience and Recent Behavior and their Relation to Content Quality on Wikipedia

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