Predicting Behavioural Patterns in Discussion Forums using Deep Learning on Hypergraphs
| Autor: | Arya, D., Rudinac, S., Worring, M., Gurrin, C., Jónsson, B.Þ., Péteri, R., Marchand-Maillet, S., Quénot, G., McGuinness, K., Guðmundsson, G.Þ., Little, S., Katsurai, M., Healy, G. |
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| Přispěvatelé: | Intelligent Sensory Information Systems (IVI, FNWI), Operations Management (ABS, FEB), Faculty of Science |
| Jazyk: | angličtina |
| Rok vydání: | 2019 |
| Předmět: | |
| Zdroj: | 2019 International Conference on Content-Based Multimedia Indexing (CBMI): proceedings : September 4-6, 2019, held at: DCU All Hallows Campus, Dublin 9, Ireland, 210-215 STARTPAGE=210;ENDPAGE=215;TITLE=2019 International Conference on Content-Based Multimedia Indexing (CBMI) CBMI |
| Popis: | Online discussion forums provide open workspace allowing users to share information, exchange ideas, address problems, and form groups. These forums feature multimodal posts and analyzing them requires a framework that can integrate heterogeneous information extracted from the posts, i.e. text, visual content and the information about user interactions with the online platform and each other. In this paper, we develop a generic framework that can be trained to identify communication behavior and patterns in relation to an entity of interest, be it user, image or text in internet forums. As the case study we use the analysis of violent online political extremism content, which has been a major challenge for domain experts. We demonstrate the generalizability and flexibility of our framework in predicting relational information between multimodal entities by conducting extensive experimentation around four practical use cases. |
| Databáze: | OpenAIRE |
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