Studying information propagation in social media is an important task with plenty of applications for business and science. Generating realistic synthetic information cascades can help the research community in developing new methods and applications, testing sociological hypotheses and different what-if scenarios by simply changing few parameters. We demonstrate WoMG, a synthetic data generator which combines topic modeling and a topic-aware propagation model to create realistic information-rich cascades, whose shape depends on many factors, including the topic of the item and its virality, the homophily of the social network, the interests of its users and their social influence.
WoMG: A Library for Word-of-Mouth Cascades Generation / Cinus, Federico; Bonchi, Francesco; Monti, Corrado; Panisson, André. - (2021), pp. 1065-1068. (Intervento presentato al convegno 14th ACM International Conference on Web Search and Data Mining, WSDM 20218 March 2021 through 12 March 2021 tenutosi a Virtual, Online) [10.1145/3437963.3441693].
WoMG: A Library for Word-of-Mouth Cascades Generation
Federico Cinus
;Francesco Bonchi
;
2021
Abstract
Studying information propagation in social media is an important task with plenty of applications for business and science. Generating realistic synthetic information cascades can help the research community in developing new methods and applications, testing sociological hypotheses and different what-if scenarios by simply changing few parameters. We demonstrate WoMG, a synthetic data generator which combines topic modeling and a topic-aware propagation model to create realistic information-rich cascades, whose shape depends on many factors, including the topic of the item and its virality, the homophily of the social network, the interests of its users and their social influence.File | Dimensione | Formato | |
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