499 research outputs found

    ChatGPT Is A User-Generated Knowledge-Sharing Killer

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    Large Language Models (LLMs), e.g., ChatGPT, is expected to reshape a broad spectrum of domains. This study examines the impact of ChatGPT on question aksing in Q&A communitits via the natural experiment. Safe-guided by supporting evidence of parallel trends, a difference-in-difference (DID) analysis suggests the launching trigger an average 2.6% reduction of question-asking on Stack Overflow, confirming a lower-search-cost-enabled substitution. Our further analysis suggests that, this substitution effect has resulted in more longer, less readable and less cognitive and hence more sophisticated questions on average. Finally, the insignificant change in the score given by viewers per question suggests no improvement in the question quality and decreased platform-wide engagement. Our moderation analysis further ascertain the types of individuals who are more susceptible to ChatGPT. Taken together, our paper suggests LLMs may threaten the survival of user-generated knowledge-sharing communities, which may further threaten the sustainable learning and long-run improvement of LLMs

    COVID-19 Community Archives and the Platformization of Digital Cultural Memory

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    In this study we aim to understand how GitHub is used by COVID-19 interest groups for organizing community archives to protect their knowledge from the Chinese government’s censorship efforts. We introduce two case studies of such COVID-19 community archives published with GitHub that appeared online in early 2020. Using public GitHub repository documentation and web archive web crawls from the Internet Archive’s Wayback Machine, we describe how these digital community archives emerge and exist on the platform, how knowledge of them circulated on other US based social media sites, and show strategies and tactics these volunteers used to keep these community archives alive, resist censorship, and guard the safety of these collections. We argue that these COVID-19 community archives are at risk because of their platform accessibility as much as the content they document, and that understanding how organizers use GitHub’s platform affordances is essential to theorizing how platforms are impacting approaches to preserving cultural memory

    Covid-19 transition, could Twitter support UK Universities?

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    This paper seeks to conceptually explore the use of social media platforms such as Twitter as a microblog to share Covid-19 prescribed knowledge through developing a conceptual framework of university ecosystem knowledge regime. The framework outlines three ecosystem artefacts; teaching, assessment, and student experience and what knowledge sharing strategies that may help representing these artefacts to the wider community of the ecosystem. The paper provides valuable practical insight to UK Universities practitioners, students and concerned stakeholders on the use of Twitter microblogs to share or retrieve knowledge required to cope with the current Covid-19 transition. The paper sheds light on the unique characteristics of knowledge sharing by UK Universities through Twitter in relation to the current Covid-19 pandemic. The paper also highlights the unconventional use of Twitter by UK Universities to share Covid-19 prescribed knowledge with its stakeholders

    Big data HE communities : could Twitter support UK universities amid the COVID-19 transition?

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    This chapter intends to explore the use of the Twitter social media platform as a microblog to share COVID-19 prescribed knowledge through observing the Twitter accounts of the five most student-populated UK universities. The chapter provides valuable practical insight to UK universities practitioners, students, and concerned stakeholders on the use of Twitter microblogs to share or retrieve knowledge required to cope with the current COVID-19 transition. The chapter sheds light on the unique characteristics of knowledge shared by UK universities through Twitter in relation to the current COVID-19 pandemic. The chapter also highlights the unconventional use of Twitter by UK universities to share COVID-19 prescribed knowledge with their stakeholders

    Deplatforming, demotion and folk theories of Big Tech persecution

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    This article examines the moderation of conspiracy narratives surrounding COVID-19 through digital methods analysis of deplatformed or demoted videos. Building upon the literature on moderation, it performs a comparison of the types of content moderated by YouTube during the early stages of the pandemic. It seeks to determine the extent to which YouTube's own moderation actions are brought in as part of the conspiratorial narratives surrounding COVID-19, while investigating how it is that moderation becomes entangled with questions of truth and visibility.This article examines YouTube’s moderation of conspiracy narratives surrounding COVID-19 through an analysis of deplatformed and demoted YouTube videos. Building upon the literature on moderation, it compares the types of content moderated by YouTube from April to October, 2020. In doing so, it seeks to determine the extent to which YouTube's own moderation actions are brought in as part of the conspiratorial narratives surrounding COVID-19, while investigating how it is that moderation becomes entangled with questions of truth and visibility.   Keywords: content moderation, conspiracy theories, YouTub
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