Leveraging burst in twitter network communities for event detection
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Leveraging burst in twitter network communities for event detection Jeffery Ansah1 · Lin Liu1 · Wei Kang1 · Jixue Liu1 · Jiuyong Li1 Received: 25 March 2019 / Revised: 19 September 2019 / Accepted: 13 January 2020 / © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Detecting protest events using social media is an important task with many useful applications to emergency services, law enforcement agencies, and other stakeholders. A plethora of research on event detection using social media has presented myriad approaches relying on tweet contents (text) to solve the event detection problem, with notable improvements over time. Despite the myriad of existing research, the use of the structural relationships among users in online Twitter network communities for event detection is rarely observed. In this work, we present a novel protest event detection framework called SensorTree. SensorTree utilizes the network structural connections among users in a community for protest event detection. The SensorTree framework tracks information propagation in Twitter network communities to model the sudden change in growth of these communities as burst for event detection. Once burst is detected, SensorTree builds a tensorized topic model to extract events. To show the prowess of SensorTree for event detection, we conduct extensive experiments on geographically diverse Twitter datasets using qualitative and quantitative evaluations. We further show the superiority of SensorTree by comparing our results to several existing state-of-the-art methods. SensorTree outperforms the baselines as well as the comparison models. The results further suggest that utilizing network community structure yields concise and accurate event detection. We also present case studies on real-world protest event to further show that SensorTree is capable of detecting events with fine granularity description without any language restrictions. Keywords SensorTree · Burst · Network community · Social media · Propagation trees · Twitter · Event detection
This article belongs to the Topical Collection: Special Issue on Web Information Systems Engineering 2018 Guest Editors: Hakim Hacid, Wojciech Cellary, Hua Wang and Yanchun Zhang Jeffery Ansah
[email protected] 1
University of South Australia, Adelaide, SA, Australia
World Wide Web
1 Introduction Social networking sites such as Twitter, Facebook, Weibo, etc., have become integral to everyday communication globally. These sites provide an interactive platform for creating and sharing information. Twitter, in particular, has become very useful for propagating of information on diverse topics such as fashion trends, political debates, sports, breaking news as well as protest events. In recent years, the advancements in Web technologies have made it possible to monitor and analyze the rich continuous flow of information on Twitter for protest event detection. Owing to these advancements, event detection using social media in recent years has gained much attenti
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