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(ICWS 2020) Characteristics of Similar-Context Trending Hashtags in Twitter: A Case Study

About This Webinar

Abstract: Twitter is a popular social networking platform that is widely used in discussing and spreading information on global events. Twitter trending hashtags have been one of the topics for researcher to study and analyze. Understanding the posting behavior patterns as the information flows increase by rapid events can help in predicting future events or detection manipulation. In this paper, we investigate similar-context trending hashtags to characterize general behavior of specific-trend and generic-trend within same context. We demonstrate an analysis to study and compare such trends based on spatial, temporal, content, and user activity. We found that the characteristics of similar-context trends can be used to predict future generic trends with analogous spatiotemporal, content, and user features. Our results show that more than 70% users participate in location-based hashtag belongs to the location of the hashtag. Generic trends aim to have more influence in users to participate than specific trends with geographical context. The retweet ratio in specific trends is higher than generic trends with more than 79%.

Authors: Eiman Alothali (United Arab Emirates University, United Arab Emirates); Abdul Kadhim Hayawi (Zayed University, United Arab Emirates); Hany Alashwal (United Arab Emirates University & College of Information Technology, United Arab Emirates)

Email: 201790016@uaeu.ac.ae, abdul.hayawi@zu.ac.ae, hany.alashwal@gmail.com

Who can view: Everyone
Webinar Price: Free
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Eiman Alothali is a PhD student in college of Information Technology in UAE University. She is studying social network features and behavior using machine learning techniques. She is interested in investigating the impact of social bots in online social networks. She has a number of publications.
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