A motif-based approach for identifying controversy

Mauro Coletto, Kiran Garimella, Aristides Gionis, Claudio Lucchese

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review

6 Citations (Scopus)
49 Downloads (Pure)


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.

Original languageEnglish
Title of host publicationProceedings of the 11th International Conference on Web and Social Media, ICWSM 2017
Number of pages4
ISBN (Electronic)9781577357889
Publication statusPublished - 2017
MoE publication typeA4 Article in a conference publication
EventInternational AAAI Conference on Web and Social Media - Montreal, Canada
Duration: 15 May 201718 May 2017
Conference number: 11


ConferenceInternational AAAI Conference on Web and Social Media
Abbreviated titleICWSM
Internet address

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