Collaboration in Online Communities: Information Processing and Decision Making

Permanent URI for this collectionhttps://hdl.handle.net/10125/107403

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    Beyond the Social Media Contents: The Role of Social Interactions in Stance Detection
    (2024-01-03) Wang, Kanlun; Zhou, Lina; Tao, Jie
    Stance detection categorizes the stance toward a specific target or topic, or other aspects of interest (e.g., a social media comment) as favor, against, or neutral. The discourse of stance detection has evolved from court debate to social media, particularly in the analyses of political, social, and health issues. Despite its long-standing history, stance detection still faces significant challenges partly due to ambiguous, diverse, and informal expressions of human language in social media. Motivated by the affordance of social interactions on social media platforms, this study aims to investigate whether social interactions are useful and how to represent and incorporate them into stance detection models effectively. To this end, we propose a framework that integrates graph learning with transformers. The empirical evaluation results with an extended benchmark dataset in the political discourse demonstrate the superior performance of the framework to the state-of-the-art baseline models and highlight the significant role of social interaction networks in stance detection. The framework can also be used to guide the efforts in social media monitoring, marketing, and informed decision-making.
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    A Dual-Platform Examination of the Relationship Between Cognitive-Experiential Values and Project Success
    (2024-01-03) Frimpong, Bright
    Reward and donation crowdfunding both leverage backers' prosocial tendencies, however they elicit differing motivations and behavioral patterns. This raises an intricate, yet underexplored question: How do emotional and cognitive values differently shape backer behavior across these seemingly similar, but fundamentally distinct platforms? Utilizing the Cognitive-Experiential Self-Theory (CEST), our study delves into the distinct impacts of experiential and cognitive values on project success across reward and donation crowdfunding. Despite the platforms' apparent similarities, our data analysis uncovers that the role of cognitive and experiential elements in driving crowd participation significantly diverges based on the platform type. Theoretically, this study expands the applicability of CEST to the crowdfunding domain, shedding light on how cognitive and experiential values intersect with platform-specific backer motivations to influence project success. Practically, our findings suggest that project founders should carefully tailor the cognitive and experiential elements in their project descriptions to better align with the motivational drivers prevalent on the specific crowdfunding platform they are utilizing.
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    On the Usefulness of Online Review Valance
    (2024-01-03) Akgul, Mehmet; Montazemi, Ali Reza; Qahri-Saremi, Hamed
    Online reviews are posted by consumers to inform others about their post-usage attitude towards the focal product/service. Often two-sided reviews that provide both pros/cons of a product/service are considered more informative than one-sided reviews. While research has looked into the usefulness of positive versus the negative aspects of the two-sided reviews, the findings are inconclusive. Some studies find negative aspects of the two-sided reviews to be more useful than positive aspects, some find the reverse to be true, and yet there are research findings that show both positive and negative aspects are equally useful. As a result, online review platforms are at loss to deal with the effects of positive/negative aspects of the reviews. Drawing on the Evaluative Space Model, our empirical study of 4705 restaurant reviews from TripAdvisor show that usefulness of reviews depends on how the attitudes of the receivers of the reviews are tilted towards positive or negative aspects of the focal product/service. And that the relationship between review usefulness and reviewers’ attitude is nonlinear.
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    Exploring the Shifting Dynamics of Information Source Selection: Situational Characteristics and the Rise of Artificial Intelligence
    (2024-01-03) Meservy, Jon; Meservy, Tom; Fadel, Kelly; Jensen, Matthew
    People often seek information from other people, including peers and experts, for various decision-making situations. Internet platforms such as online discussion forums have greatly expanded access to these human information sources. However, the rapid raise and prevalence of ChatGPT and other large language models may shift the focus away from these traditional human sources toward artificial intelligence. Research has shown that information source selection depends in part on the characteristics of the situation for which information is sought. In this paper we investigate situational characteristics that impact the selection of peers, experts, or ChatGPT as an information source. The data reveals that the selection of ChatGPT as an information source is tied to different characteristics than that of peers or experts, implying that AI is not yet a full substitute for human information sources.