WhoSNext: Recommending Twitter Users to Follow Using a Spreading Activation Network Based Approach

Research output: Chapter in Book/Report/Conference proceedingConference contribution


The huge number of modern social network users has made the web a fertile ground for the growth and development of a plethora of recommender systems. To date, recommending a new user profile X to a given user U that could be interested in creating a relationship with X has been tackled using techniques based on content analysis, existing friendship relationships and other pieces of information coming from different social networks or websites. In this paper we propose a recommending architecture-called WhoSNext (WSN)-tested on Twitter and which aim is promoting the creation of new relationships among users. As recent researches show, this is an interesting recommendation problem: for a given user U, find which other user might be proposed to U as a new friend. Instead of conducting a study based on a semantic approach (e.g. analyzing tweet content), the proposed algorithm exploits a graph created from a set of Twitter users called seeds. In this work-and, to the best of our knowledge, for the first time-this issue is addressed using only user ID for building a particular Spreading Activation Network. This network was firstly trained and then tested on a set consisting of over 400,000 real users. Experimental results show that this approach outperforms the results obtained from many well-known state-of-the-art systems, which are much more expensive in terms of either data preprocessing or computational resources.
Original languageEnglish
Title of host publicationIEEE International Conference on Data Mining Workshops, ICDMW
Number of pages9
Publication statusPublished - 2020

Publication series


All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Software


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