A motif-based approach for identifying controversy

Among the topics discussed in Social Media, some lead to controversy. A number of recent studies have focused on the problem of identifying controversy in social media mostly based on the analysis of textual content or rely on global network structure. Such approaches have strong limitations due to the difficulty of understanding natural language, and of investigating the global network structure. In this work we show that it is possible to detect controversy in social media by exploiting network motifs, i.e., local patterns of user interaction. The proposed approach allows for a language-independent and fine-grained and efficientto- compute analysis of user discussions and their evolution over time. The supervised model exploiting motif patterns can achieve 85% accuracy, with an improvement of 7% compared to baseline structural, propagation-based and temporal network features.

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| openaire: EC/H2020/654024/EU//SoBigData

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Coletto, M, Garimella, K, Gionis, A & Lucchese, C 2017, A motif-based approach for identifying controversy. in Proceedings of the 11th International Conference on Web and Social Media, ICWSM 2017. AAAI Press, pp. 496-499, International AAAI Conference on Web and Social Media, Montreal, Canada, 15/05/2017. < https://aaai.org/ocs/index.php/ICWSM/ICWSM17/paper/view/15653/14838 >

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https://urn.fi/URN:NBN:fi:aalto-201809064984

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[article-cris] Perustieteiden korkeakoulu / SCI

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A motif-based approach for identifying controversy

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