Collaboration in Online Communities: Information Processing and Decision Making

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https://hdl.handle.net/10125/72117

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    When to Signal? The Contextual Conditions for Career-Motivated User Contributions in Online Collaboration Communities
    ( 2021-01-05) Lee, Jeongsik ”Jay” ; Park, Hyunwoo ; Zaggl, Michael
    This paper examines the contextual conditions for users’ career concern as a motivational driver of contributions in online collaboration communities. On the data of user-level activities from a computer programming-related online Q&A community (Stack Overflow), merged with job-market data for software-developer, we find robust evidence of a positive association between individual users’ career concern and their contributions. More important, we find that this positive relationship is further strengthened through the contextual conditions: the number of vacancies in the job market, the expected salaries from these jobs, and the transparency in the flow of career-related information within the community. We contribute to the literature on motivation in online collaboration communities. Our study thus offers insight into how career concern can be effectively utilized to motivate contributors in these communities. Our findings also foreshadow a possible paradigm change by characterizing online collaboration communities as institutions of career concern and skill signaling.
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    Social Capital in Online Temporary Organizations: Addressing Critical, Complex Tasks through Deliberation
    ( 2021-01-05) Joyce, Elisabeth ; Ozturk, Pinar ; Pike, Jacqueline
    Temporary organizations—small, task-focused, time-bound, agile groups—exist in mass collaborations to address tasks outside of existing procedures. Given that mass collaborations are informal and voluntary, this study explores the impact of social network attributes (cohesion and diversity) in temporary organizations on task completion. We suggest that participants’ prior shared experience and demonstrated knowledge of the larger organization in online temporary organizations, traits of cohesion, and working less often with the same people, evidence of diversity, lead to greater likelihood of successful task completion. Contrary to predictions, however, the less consistent the participant contributions, the lower the likelihood of successful task completion.
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    Expert vs. Peer: The Role of Situational Characteristics in Electronic Networks of Practice
    ( 2021-01-05) Jensen, Matthew ; Matthews, Michael ; Meservy, Thomas ; Fadel, Kelly
    Individuals turn to online forums sponsored by Electronic Networks of Practice (ENPs) to acquire information on a range of topics; yet, quality and relevancy of such information can vary greatly. To assist information seekers, many ENP forums incorporate contextual cues that provide signals originating from both expert and lay forum users about the quality of solutions. While extant research has explored how these cue sources influence information filtering on ENP forums, results on their relative impact are fragmented and often contradictory. This paper advances research in this domain by employing situation theory to examine how six situational characteristics influence individuals’ propensity to rely on peer vs. expert recommendations. Results demonstrate that users rely more on expert recommendations when seeking information for situations that they perceive as stressful, task-oriented, or requiring greater cognitive processing, while peer recommendations are preferred for situations perceived as fun. Implications for research and practice are discussed.
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    EmoG- Towards Emojifying Gmail Conversations
    ( 2021-01-05) Venigalla, Akhila Sri Manasa ; Chimalakonda, Sridhar
    Emails are one of the most frequently used medium of communication in the present day across multiple domains including industry and educational institutions. Understanding sentiments being expressed in an email could have a considerable impact on the recipients' action or response to the email. However, it is difficult to interpret emotions of the sender from pure text in which emotions are not explicitly present. Researchers have tried to predict customer attrition by integrating emails in client-company environment with emotions. However, most of the existing works deal with static assessment of email emotions. Presenting sentiments of emails dynamically to the reader could help in understanding senders' emotion and as well have an impact on readers' action. Hence, in this paper, we present EmoG as a Google Chrome Extension which is intended to support university students. It augments emails with emojis based on the sentiment being conveyed in the email, which might also offer faster overview of email sentiments and act as tags that could help in automatic sorting and processing of emails. Currently, EmoG has been developed to support Gmail inbox on a Google Chrome browser, and could be extended to other inboxes and browsers with ease. We have conducted a user survey with 15 university students to understand the usefulness of EmoG and received positive feedback.
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