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Predicting emotional reaction in social networks.

Clos, Jérémie; Bandhakavi, Anil; Wiratunga, Nirmalie; Cabanac, Guillaume


Jérémie Clos

Anil Bandhakavi

Guillaume Cabanac


Joemon M Jose

Claudia Hauff

Ismail Sengor Altıngovde

Dawei Song

Dyaa Albakour

Stuart Watt

John Tait


Online content has shifted from static and document-oriented to dynamic and discussion-oriented, leading users to spend an increasing amount of time navigating online discussions in order to participate in their social network. Recent work on emotional contagion in social networks has shown that information is not neutral and affects its receiver. In this work, we present an approach to detect the emotional impact of news, using a dataset extracted from the Facebook pages of a major news provider. The results of our approach significantly outperform our selected baselines.

Start Date Apr 8, 2017
Publication Date Apr 8, 2017
Print ISSN 0302-9743
Electronic ISSN 1611-3349
Publisher Springer (part of Springer Nature)
Pages 527-533
Series Title Lecture notes in computer science
Series Number 10193
Series ISSN 1611-3349
ISBN 9783319566078
Institution Citation CLOS, J., BANDHAKAVI, A., WIRATUNGA, N. and CABANAC, G. 2017. Predicting emotional reaction in social networks. In Jose, J.M., Hauff, C., Altingovde, I.S., Song, D., Albakour, D., Watt, S. and Tait, J. (eds.) Advances in information retrieval: proceedings of the 39th European conference on information retrieval (ECIR 2017), 8-13 April 2017, Aberdeen, UK. Lecture notes in computer science, 10193. Cham: Springer [online], pages 527-533. Available from:
Keywords Social networks ; Emotional analysis ; Emotional triggers ; Sentiment analysis


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