The Strength of Considering Tie Strength in Social Interest Profiling

  • Asma Chader Laboratoire de la Communication dans les Systèmes Informatiques (LCSI), Ecole Nationale Supérieure d’Informatique (ESI), BP 68M, 16309, Oued-Smar, Algiers, Algeria https://orcid.org/0000-0002-0037-5529
  • Hamid Haddadou Laboratoire de la Communication dans les Systèmes Informatiques (LCSI), Ecole Nationale Supérieure d’Informatique (ESI), BP 68M, 16309, Oued-Smar, Algiers, Algeria https://orcid.org/0000-0003-0824-0124
  • Leila Hamdad Laboratoire de la Communication dans les Systèmes Informatiques (LCSI), Ecole Nationale Supérieure d’Informatique (ESI), BP 68M, 16309, Oued-Smar, Algiers, Algeria https://orcid.org/0000-0003-4515-5519
  • Walid-Khaled Hidouci Laboratoire de la Communication dans les Systèmes Informatiques (LCSI), Ecole Nationale Supérieure d’Informatique (ESI), BP 68M, 16309, Oued-Smar, Algiers, Algeria https://orcid.org/0000-0002-8290-1093
Keywords: Social profiling, User profile, Relationship strength, Weighted social networks, Egocentric networks

Abstract

With the emergence of social networking platforms and great amount of generated content, analyzing people interactions and behaviour raises new opportunities for several applications such as user interest profiling. In this context, this paper highlights the importance of considering relationship strength to infer more refined and relevant interests from user’s direct neighbourhood. We propose WeiCoBSP, a Weight-aware Community-Based Social Profiling approach that leverages strength of ego-friend and friend-friend relationships. The former, describing connections with the profiled user, allows to identify most relevant people from whom to infer worthwhile interests. The latter qualifies connections among user’s neighbourhood and enables depicting the most realistic community structure of the network. We present an empirical evaluation performed on real world co-authorship networks, validating our approach. Experimental results demonstrate the ability of WeiCoBSP to infer user’s interest accurately, improving greatly the unweighted CoBSP process but also results of experiments assessing separately ego-friend and friend-friend relationships strength.

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Author Biographies

Asma Chader, Laboratoire de la Communication dans les Systèmes Informatiques (LCSI), Ecole Nationale Supérieure d’Informatique (ESI), BP 68M, 16309, Oued-Smar, Algiers, Algeria

Asma Chader is a PhD student at Ecole Nationale Supérieure d’Informatique (ESI), Algiers, Algeria. She received her Engineering and Master’s degree in 2015 from the same school. Her research interests include data mining, social network analysis and sentiment analysis.

Hamid Haddadou, Laboratoire de la Communication dans les Systèmes Informatiques (LCSI), Ecole Nationale Supérieure d’Informatique (ESI), BP 68M, 16309, Oued-Smar, Algiers, Algeria

Hamid Haddadou is a Lecturer at Ecole Nationale Supérieure d’Informatique (ESI), Algiers, Algeria. He is the head of Applied Mathematics team at the “Laboratoire de Communication dans les Systèmes Informatique”, LCSI (Laboratory of Communication in Computer Systems). He had his PhD, and Magister degree in Mathematics at TheăUniversity of Science and Technology -ŰăHouari Boumediene USTHB (Algiers, Algeria). His research interests include mainly networks modelling, image processing and multi-scale mathematic modelling.

Leila Hamdad, Laboratoire de la Communication dans les Systèmes Informatiques (LCSI), Ecole Nationale Supérieure d’Informatique (ESI), BP 68M, 16309, Oued-Smar, Algiers, Algeria

Leila Hamdad is a Lecturer at Ecole Nationale Supérieure en Informatique (ESI), Algiers, Algeria. She is member of the Laboratoire de Communication dans les Systèmes Informatique, LCSI, ESI (Laboratory of Communication in Computer Systems) in Applied mathematics team. She had her PhD on Computer Science in the same school and a Magister degree in Mathematics at TheaăUniversity of Science and Technology –ăHouari Boumediene USTHB (Algiers, Algeria). Her topics of interest are related to data mining, machine learning, spatial statistics and parallel computing.

Walid-Khaled Hidouci, Laboratoire de la Communication dans les Systèmes Informatiques (LCSI), Ecole Nationale Supérieure d’Informatique (ESI), BP 68M, 16309, Oued-Smar, Algiers, Algeria

Walid-Khaled Hidouci is currently Associate Professor at Ecole Nationale Supérieure dŠInformatique (ESI), Algiers, Algeria since 1993. His areas of interest mainly concern database systems, data structures, operating systems and parallel programming. Since 2010, he has been leading the “Advanced Databases” (BDA) team at the “Laboratoire de Communication dans les Systèmes Informatique”, LCSI, ESI (Laboratory of Communication in Computer Systems).

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Published
2020-08-01
Section
Articles