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AMIR: A Multi-agent Approach for Influence Detection in Social Networks

  • Conference paper
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Distributed Computing and Artificial Intelligence, 20th International Conference (DCAI 2023)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 740))

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Abstract

The omnipresence of social networks makes their analysis essential. Two lines of research have attracted a lot of interest in the analysis of social networks in recent years: Community detection and influence maximization. There are mainly two approaches to studying influence in a social network context: centralized and agent-based. Despite this interest, much of this research has focused on structural links between nodes, as well as interactions. But the details of the semantics of communication that takes place between the nodes of a social network have not been studied much. The main contribution of this paper is to deal with the different interactions between members of a social network. To accomplish this, different methods are used, such as opinion mining, to abstract the social network and to allow the identification of the influencers. We propose to develop a multi-agent architecture to solve the problem of detecting influential elements. We associate with each node of the social network an agent (manager of the node). We develop coordination mechanisms between these agents to conduct the voting process in order to determine the influential elements in the network.

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Author information

Authors and Affiliations

  1. Crestic Lab, University of Reims Champagne-Ardenne, Reims, France

    Chaima Messaoudi & Zahia Guessoum

  2. Mars Lab, University of Sousse, Hammam Sousse, Tunisia

    Chaima Messaoudi & Lotfi Ben Romdhane

Authors
  1. Chaima Messaoudi
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  2. Lotfi Ben Romdhane
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  3. Zahia Guessoum
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Corresponding author

Correspondence to Chaima Messaoudi .

Editor information

Editors and Affiliations

  1. ETSII / CETINIA, Universidad Rey Juan Carlos, Madrid, Madrid, Spain

    Sascha Ossowski

  2. Politechnika ÅšlÄ…ska Kielce, Kielce University of Technology, Santa Cruz, Poland

    Pawel Sitek

  3. Department of Informatics, Engineering School, University of Minho, Braga, Portugal

    Cesar Analide

  4. Departamento de Engenharia Informática, Polytechnic Institute of Porto, Porto, Portugal

    Goreti Marreiros

  5. BISITE, University of Salamanca, Salamanca, Salamanca, Spain

    Pablo Chamoso

  6. BISITE, University of Salamanca, Salamanca, Salamanca, Spain

    Sara Rodríguez

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Messaoudi, C., Romdhane, L.B., Guessoum, Z. (2023). AMIR: A Multi-agent Approach for Influence Detection in Social Networks. In: Ossowski, S., Sitek, P., Analide, C., Marreiros, G., Chamoso, P., Rodríguez, S. (eds) Distributed Computing and Artificial Intelligence, 20th International Conference. DCAI 2023. Lecture Notes in Networks and Systems, vol 740. Springer, Cham. https://doi.org/10.1007/978-3-031-38333-5_25

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