Social media users readily share their preferences, life events, sentiment and opinions, and implicitly signal their thoughts, feelings, and psychological behavior. This makes social media a viable source of information to accurately and effectively mine users' interests with the hopes of enabling more effective user engagement, better quality delivery of appropriate services and higher user satisfaction. In this tutorial, we cover five important aspects related to the effective mining of user interests: (1) the foundations of social user interest modeling, such as information sources, various types of representation models and temporal features, (2) techniques that have been adopted or proposed for mining user interests, (3) different evaluation methodologies and benchmark datasets, (4) different applications that have been taking advantage of user interest mining from social media platforms, and (5) existing challenges, open research questions and exciting opportunities for further work.

Mining User Interests from Social Media / Zarrinkalam, F.; Piao, G.; Faralli, S.; Bagheri, E.. - (2020), pp. 3519-3520. (Intervento presentato al convegno 29th ACM International Conference on Information and Knowledge Management, CIKM 2020 tenutosi a irl) [10.1145/3340531.3412167].

Mining User Interests from Social Media

Faralli S.
Co-primo
;
2020

Abstract

Social media users readily share their preferences, life events, sentiment and opinions, and implicitly signal their thoughts, feelings, and psychological behavior. This makes social media a viable source of information to accurately and effectively mine users' interests with the hopes of enabling more effective user engagement, better quality delivery of appropriate services and higher user satisfaction. In this tutorial, we cover five important aspects related to the effective mining of user interests: (1) the foundations of social user interest modeling, such as information sources, various types of representation models and temporal features, (2) techniques that have been adopted or proposed for mining user interests, (3) different evaluation methodologies and benchmark datasets, (4) different applications that have been taking advantage of user interest mining from social media platforms, and (5) existing challenges, open research questions and exciting opportunities for further work.
2020
29th ACM International Conference on Information and Knowledge Management, CIKM 2020
explicit interest; future interest; implicit interest; social media; user interest mining
04 Pubblicazione in atti di convegno::04b Atto di convegno in volume
Mining User Interests from Social Media / Zarrinkalam, F.; Piao, G.; Faralli, S.; Bagheri, E.. - (2020), pp. 3519-3520. (Intervento presentato al convegno 29th ACM International Conference on Information and Knowledge Management, CIKM 2020 tenutosi a irl) [10.1145/3340531.3412167].
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11573/1622815
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