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  • × year_i:[2020 TO 2030}
  1. Zhang, X.; Wang, D.; Tang, Y.; Xiao, Q.: How question type influences knowledge withholding in social Q&A community (2023) 0.14
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    Abstract
    Social question-and-answer (Q&A) communities are becoming increasingly important for knowledge acquisition. However, some users withhold knowledge, which can hinder the effectiveness of these platforms. Based on social exchange theory, the study investigates how different types of questions influence knowledge withholding, with question difficulty and user anonymity as boundary conditions. Two experiments were conducted to test hypotheses. Results indicate that informational questions are more likely to lead to knowledge withholding than conversational ones, as they elicit more fear of negative evaluation and fear of exploitation. The study also examines the interplay of question difficulty and user anonymity with question type. Overall, this study significantly extends the existing literature on counterproductive knowledge behavior by exploring the antecedents of knowledge withholding in social Q&A communities.
    Date
    22. 9.2023 13:51:47
  2. Gabler, S.: Vergabe von DDC-Sachgruppen mittels eines Schlagwort-Thesaurus (2021) 0.10
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    Content
    Master thesis Master of Science (Library and Information Studies) (MSc), Universität Wien. Advisor: Christoph Steiner. Vgl.: https://www.researchgate.net/publication/371680244_Vergabe_von_DDC-Sachgruppen_mittels_eines_Schlagwort-Thesaurus. DOI: 10.25365/thesis.70030. Vgl. dazu die Präsentation unter: https://www.google.com/url?sa=i&rct=j&q=&esrc=s&source=web&cd=&ved=0CAIQw7AJahcKEwjwoZzzytz_AhUAAAAAHQAAAAAQAg&url=https%3A%2F%2Fwiki.dnb.de%2Fdownload%2Fattachments%2F252121510%2FDA3%2520Workshop-Gabler.pdf%3Fversion%3D1%26modificationDate%3D1671093170000%26api%3Dv2&psig=AOvVaw0szwENK1or3HevgvIDOfjx&ust=1687719410889597&opi=89978449.
  3. Kang, M.: Dual paths to continuous online knowledge sharing : a repetitive behavior perspective (2020) 0.09
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    Abstract
    Purpose Continuous knowledge sharing by active users, who are highly active in answering questions, is crucial to the sustenance of social question-and-answer (Q&A) sites. The purpose of this paper is to examine such knowledge sharing considering reason-based elaborate decision and habit-based automated cognitive processes. Design/methodology/approach To verify the research hypotheses, survey data on subjective intentions and web-crawled data on objective behavior are utilized. The sample size is 337 with the response rate of 27.2 percent. Negative binomial and hierarchical linear regressions are used given the skewed distribution of the dependent variable (i.e. the number of answers). Findings Both elaborate decision (linking satisfaction, intentions and continuance behavior) and automated cognitive processes (linking past and continuance behavior) are significant and substitutable. Research limitations/implications By measuring both subjective intentions and objective behavior, it verifies a detailed mechanism linking continuance intentions, past behavior and continuous knowledge sharing. The significant influence of automated cognitive processes implies that online knowledge sharing is habitual for active users. Practical implications Understanding that online knowledge sharing is habitual is imperative to maintaining continuous knowledge sharing by active users. Knowledge sharing trends should be monitored to check if the frequency of sharing decreases. Social Q&A sites should intervene to restore knowledge sharing behavior through personalized incentives. Originality/value This is the first study utilizing both subjective intentions and objective behavior data in the context of online knowledge sharing. It also introduces habit-based automated cognitive processes to this context. This approach extends the current understanding of continuous online knowledge sharing behavior.
    Date
    20. 1.2015 18:30:22
  4. Kang, M.: Motivational affordances and survival of new askers on social Q&A sites : the case of Stack Exchange network (2022) 0.08
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    Abstract
    Social question-and-answer (Q&A) sites are platforms where users can freely ask, share, and rate knowledge. For the sustainable growth of social Q&A sites, maintaining askers is as critical as maintaining answerers. Based on motivational affordances theory and self-determination theory, this study explores the influence of the design elements of social Q&A sites (i.e., upvotes, downvotes, edits, user profile, and comments) on the survival of new askers. In addition, the moderating effect of having an alternative experience is examined. Online data on 25,000 new askers from the top five Q&A sites in the Technology category of the Stack Exchange network are analyzed using logistic regression. The results show that the competency- and autonomy-related design features of social Q&A sites motivate new askers to continue participating. Surprisingly, having an alternative experience shows a negative moderating effect, implying that alternative experiences increase switching costs in the Stack Exchange network. This study provides valuable insights for administrators of social Q&A sites as well as academics.
  5. Zhou, Q.; Lee, C.S.; Sin, S.-C.J.; Lin, S.; Hu, H.; Ismail, M.F.F. Bin: Understanding the use of YouTube as a learning resource : a social cognitive perspective (2020) 0.07
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    Date
    20. 1.2015 18:30:22
  6. Zhao, Y.C.; Peng, X.; Liu, Z.; Song, S.; Hansen, P.: Factors that affect asker's pay intention in trilateral payment-based social Q&A platforms : from a benefit and cost perspective (2020) 0.06
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    Abstract
    More and more social Q&A platforms are launching a new business model to monetize online knowledge. This monetizing process introduces a more complicated cost and benefit tradeoff to users, especially for askers' concerns. Much of the previous research was conducted in the context of free-based Q&A platform, which hardly explains the triggers that motivate askers' pay intention. Based on the theories of social exchange and social capital, this study aims to identify and examine the antecedents of askers' pay intention from the perspective of benefit and cost. We empirically test our predictions based on survey data collected from 322 actual askers in a well-known trilateral payment-based social Q&A platform in China. The results by partial least squares (PLS) analysis indicate that besides noneconomic benefits including self-enhancement, social support, and entertainment, financial factors such as cost and benefit have significant influences on the perceived value of using trilateral payment-based Q&A platforms. More important, we further identify that the effect of financial benefit is moderated by perceived reciprocity belief, and the effect of perceived value is moderated by perceived trust in answerers. Our findings contribute to the previous literature by proposing a theoretical model that explains askers' behavioral intention, and the practical implications for payment-based Q&A service providers and participants.
  7. Wu, Q.; Lee, C.S.; Goh, D.H.-L.: Understanding user-generated questions in social Q&A : a goal-framing approach (2023) 0.05
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    Abstract
    In social Q&A, user-generated questions can be viewed as goal expressions shaping the responses. Several studies have identified askers' goals from questions. However, it remains unclear how questions set goals for responders. To fill this gap, this research applies goal-framing theory. Goal-frames influence responses by attracting responders' attention to different goals. Eight question cues are used to identify gain, hedonic and normative goal-frames. A total of 14,599 posts are collected. To investigate the influence of goal-frames, response networks are constructed. Results reveal that gain goal-frames attract interactions with questions, while hedonic, and normative goal-frames promote interactions among responses. Further, topic types influence the effects of goal-frames. Gain goal-frames increase interactions with questions in Science, Technology, Engineering, and Mathematics (STEM) topics while hedonic and normative goal-frames attract interactions in non-STEM topics. This research leverages responders' perspectives to explain responses to questions, which are influenced by the goals set up by question cues. Beyond that, our findings enrich the empirical knowledge of social Q&A topics, revealing that the influence of questions varies across STEM and non-STEM topics because the question cues for specifying goals are different in the two topics. Our research opens new directions to investigate questions from responders' perspectives.
  8. Liu, Q.; Yang, Z.; Cai, X.; Du, Q.; Fan, W.: ¬The more, the better? : The effect of feedback and user's past successes on idea implementation in open innovation communities (2022) 0.04
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  9. Du, Q.; Li, J.; Du, Y.; Wang, G.A.; Fan, W.: Predicting crowdfunding project success based on backers' language preferences (2021) 0.03
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  10. Sun, X.; Zhou, X.; Wang, Q.; Sharples, S.: Investigating the impact of emotions on perceiving serendipitous information encountering (2022) 0.03
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  11. Geras, A.; Siudem, G.; Gagolewski, M.: Time to vote : temporal clustering of user activity on Stack Overflow (2022) 0.03
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    Abstract
    Question-and-answer (Q&A) sites improve access to information and ease transfer of knowledge. In recent years, they have grown in popularity and importance, enabling research on behavioral patterns of their users. We study the dynamics related to the casting of 7 M votes across a sample of 700 k posts on Stack Overflow, a large community of professional software developers. We employ log-Gaussian mixture modeling and Markov chains to formulate a simple yet elegant description of the considered phenomena. We indicate that the interevent times can naturally be clustered into 3 typical time scales: those which occur within hours, weeks, and months and show how the events become rarer and rarer as time passes. It turns out that the posts' popularity in a short period after publication is a weak predictor of its overall success, contrary to what was observed, for example, in case of YouTube clips. Nonetheless, the sleeping beauties sometimes awake and can receive bursts of votes following each other relatively quickly.
  12. Qi, Q.; Hessen, D.J.; Heijden, P.G.M. van der: Improving information retrieval through correspondenceanalysis instead of latent semantic analysis (2023) 0.03
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  13. Noever, D.; Ciolino, M.: ¬The Turing deception (2022) 0.03
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    Source
    https%3A%2F%2Farxiv.org%2Fabs%2F2212.06721&usg=AOvVaw3i_9pZm9y_dQWoHi6uv0EN
  14. Wang, H.; Song, Y.-Q.; Wang, L.-T.: Memory model for web ad effect based on multimodal features (2020) 0.03
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  15. Hong, H.; Ye, Q.: Crowd characteristics and crowd wisdom : evidence from an online investment community (2020) 0.03
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  16. Makri, S.; Turner, S.: "I can't express my thanks enough" : the "gratitude cycle" in online communities (2020) 0.03
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    Abstract
    Gratitude is a fundamental aspect of social interaction that positively influences emotional and social well-being. It is also crucial for promoting online community health by motivating participation. However, how gratitude occurs and can be encouraged in online communities is not yet well understood. This exploratory study investigated how online community users experience gratitude, focusing on how gratitude expression and acknowledgment occurs, can break down or can be reinforced. Semistructured Critical Incident interviews were conducted with 8 users of various online communities, including discussion and support groups, social Q&A sites, and review sites, eliciting 17 memorable examples of giving and receiving thanks online. The findings gave rise to a process model of gratitude in online communities-the "gratitude cycle," which provides a detailed, holistic understanding of the experience of gratitude online that can inform the design of online community platforms that aim to motivate users to perpetuate the cycle. An enriched understanding of gratitude in online communities can help ensure future platforms better support the expression and acknowledgment of thanks, encouraging participation.
  17. He, C.; Wu, J.; Zhang, Q.: Research leadership flow determinants and the role of proximity in research collaborations (2020) 0.03
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Languages

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  • d 29

Types

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  • el 20
  • m 2
  • p 2
  • x 1
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