Modelling Formation of Online Temporal Communities
| العنوان: | Modelling Formation of Online Temporal Communities |
|---|---|
| المؤلفون: | Isa Inuwa-Dutse |
| المصدر: | WWW (Companion Volume) |
| بيانات النشر: | ACM Press, 2018. |
| سنة النشر: | 2018 |
| مصطلحات موضوعية: | Social and Information Networks (cs.SI), FOS: Computer and information sciences, Event monitoring, Clique, Physics - Physics and Society, Event (computing), Computer science, FOS: Physical sciences, Computer Science - Social and Information Networks, 020206 networking & telecommunications, Cohesion (computer science), Physics and Society (physics.soc-ph), 02 engineering and technology, Data science, Metadata, Group cohesiveness, 0202 electrical engineering, electronic engineering, information engineering, 020201 artificial intelligence & image processing, Social media, Social network analysis |
| الوصف: | Contemporary social media networks can be viewed as a break to the early two-step flow model in which influential individuals act as intermediaries between the media and the public for information diffusion. Today's social media platforms enable users to both generate and consume online contents. Users continuously engage and disengage in discussions with varying degrees of interaction leading to formation of distinct online communities. Such communities are often formed at high-level either based on metadata, such as hashtags on Twitter, or popular content triggered by few influential users. These online communities often do not reflect true connectivity and lack the cohesiveness of traditional communities. In this study, we investigate real-time formation of temporal communities on Twitter. We aim at defining both high and low levels connections and to reveal the magnitude of clustering cohesion on temporal basis. Inspired by a real-life event center sitting arrangement scenario, the proposed method aims to cluster users into distinct and cohesive online temporal communities. Membership to a community relies on intrinsic tweet properties to define similarity as the basis for interaction networks. The proposed method can be useful for local event monitoring and clique-based marketing among other applications. 5 pages, 7 figures |
| URL الوصول: | https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6727d8ba5bcb2074c3a27aed597611ed https://doi.org/10.1145/3184558.3186577 |
| حقوق: | OPEN |
| رقم الأكسشن: | edsair.doi.dedup.....6727d8ba5bcb2074c3a27aed597611ed |
| قاعدة البيانات: | OpenAIRE |
| الوصف غير متاح. |