A pattern-based approach for an early detection of popular Twitter accounts
Authors: 
Jonathan Debure, Stephan Brunessaux, Camelia Constantin, Cédric du MouzaAuthors Info & Claims
Jonathan Debure, Stephan Brunessaux, Camelia Constantin, Cédric du MouzaAuthors Info & ClaimsArticle No.: 10, Pages 1 - 9
Abstract
Social networks (SN) are omnipresent in our lives today. Not all users have the same behaviour on these networks. If some have a low activity, rarely posting messages and following few users, some others at the other extreme have a significant activity, with many followers and regularly posts. The important role of these popular SN users makes them the target of many applications for example for content monitoring or advertising. It is therefore relevant to be able to predict as soon as possible which SN users will become popular.
In this work, we propose a technique for early detection of such users based on the identification of characteristic patterns. We present an index, H2M, which allows a scaling up of our approach to large social networks. We also describe our first experiments that confirm the validity of our approach.
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Published: 25 August 2020
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IDEAS 2020
IDEAS 2020: 24th International Database Engineering & Applications Symposium
August 12 - 14, 2020
Seoul, Republic of Korea
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IDEAS '20 Paper Acceptance Rate 27 of 57 submissions, 47%;
Overall Acceptance Rate 74 of 210 submissions, 35%
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