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Inferring User Interests in Microblogging Social Networks: A Survey

Publication Type: 
Refereed Review Article
With the growing popularity of microblogging services such as Twitter in recent years, an increasing number of users are using these services in their daily lives. The huge volume of information generated by users raises new opportunities in various applications and areas. Inferring user interests plays a signifi cant role in providing personalized recommendations on microblogging services, and also on third-party applications providing social logins via these services, especially in cold-start situations. In this survey, we review user modeling strategies with respect to inferring user interests from previous studies. To this end, we focus on four dimensions of inferring user interest profi les: (1) data collection, (2) representation of user interest profi les, (3) construction and enhancement of user interest profi les, and (4) the evaluation of the constructed profi les. Through this survey, we aim to provide an overview of state-of-the-art user modeling strategies for inferring user interest profi les on microblogging social networks with respect to the four dimensions. For each dimension, we review and summarize previous studies based on speci fied criteria. Finally, we discuss some challenges and opportunities for future work in this research domain.
Digital Object Identifer (DOI): 
Publication Status: 
In Press
Date Accepted for Publication: 
Friday, 10 August, 2018
Publication Date: 
Research Group: 
National University of Ireland, Galway (NUIG)
Open access repository: 
Publication document: