SoMePeAS: Social Media for Personalization And Search

Special issue of the “Information Retrieval Journal” (Springer)

Call for papers:

Social media platforms have become powerful tools to collect the preferences of the users and get to know them more. In order to build profiles about what the users like or dislike, a system does not only have to rely on explicitly given preferences (e.g., ratings) or on implicitly collected data (e.g., from the browsing sessions). In the middle, there lie opinions and preferences expressed through likes, textual comments, click/view logs, following preferences, digital conversations, and posted content. Moreover, the social network itself can provide information on who influences whom.

In order to improve the web experience of the users, classic personalization technologies (e.g., recommender systems) and search engines usually rely on static schemes. Users are allowed to express ratings in a fixed range of values for a given catalogue of products, or to express a query that usually returns the same set of webpages/products for all the users.

Being able to mine usage and collaboration patterns in social media and to analyze the content generated by the users opens new frontiers in the generation of personalization services and in the improvement of search engines. Moreover, recent technological advances, such as deep learning, are able to provide a context to the analyzed data (e.g., Google's word2vec provides a vector representation of the words in a corpus, considering the context in which a word has been used).

This special issue solicits novel papers that exploit social media on a broad range of topics, including, but not limited to:

  • Recommender systems;
  • Search and tagging;
  • Query expansion;
  • User modeling and profiling;
  • Advertising and ad targeting;
  • Content classification, categorization, and clustering;
  • Using social network features/community detection algorithms for personalization and search purposes;
  • Event/topic detection over heterogeneous social sources.

Submission guidelines:

Paper submissions must conform to the Information Retrieval Journal format guidelines.

Manuscripts must be submitted to the online submission system (select option S.I. : Social Media for Personalization and Search in the article type).

Submissions to this Special Issue must represent original material that has been neither submitted to, nor published in, any other journal. A submission based on one or more papers that appeared elsewhere should have at least 30% of novel valuable content that extends the original work (the original papers should be referenced and the novel contributions should be clearly stated in the submitted paper).

Guest editors:

Ludovico Boratto:

Digital Humanities Department, Eurecat (Technology Center of Catalonia)

Barcelona – Spain (

Ludovico Boratto is researcher in the Digital Humanities research group at Eurecat. His research interests focus on Data Mining and Machine Learning approaches, mostly applied to recommender systems and social network analysis. In 2012 he got a Ph.D. at the University of Cagliari, where he was a research assistant until May 2016. In 2010 and 2014 he spent 10 months at Yahoo! Research in Barcelona as a visiting researcher. He is member of the ACM.

Andreas Kaltenbrunner:

Digital Humanities Department, NTENT

Barcelona – Spain (

Andreas Kaltenbrunner is Head of the Digital Humanities research group at Eurecat. He also holds a position as assistant professor at the Department of Information and Communication Technologies - University Pompeu Fabra. His research is centred on social media and social network analysis. He uses methods from computer science and the study of complex systems to resolve sociological research questions. Dr. Kaltenbrunner obtained his Ph.D. from the University Pompeu Fabra in Computer Science and Digital Communication in 2008.

Giovanni Stilo

Dipartimento di Informatica, Sapienza Università di Roma

Rome – Italy (

Giovanni Stilo is an assistant professor at the Department of Computer Science - Sapienza University of Rome. Dr. Stilo obtained his Ph.D. from the University of Aquila in Computer Science and Applications in 2013. He is mainly involved on the study of temporal mining, network analysis over social source, semantic oriented recommender systems, and centrality measures in multiplex networks. He was previously contractor with the Web Mining Group of Yahoo! Lab in Barcelona.


For enquires regarding the special issue, please send an email to all the guest editors at : | |