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Analyzing users’ activity in online social networks over time through a multi-agent framework

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Abstract

The number of people and organizations using online social networks as a new way of communication is continually increasing. Messages that users write in networks and their interactions with other users leave a digital trace that is recorded. In order to understand what is going on in these virtual environments, it is necessary systems that collect, process, and analyze the information generated. The majority of existing tools analyze information related to an online event once it has finished or in a specific point of time (i.e., without considering an in-depth analysis of the evolution of users’ activity during the event). They focus on an analysis based on statistics about the quantity of information generated in an event. In this article, we present a multi-agent system that automates the process of gathering data from users’ activity in social networks and performs an in-depth analysis of the evolution of social behavior at different levels of granularity in online events based on network theory metrics. We evaluated its functionality analyzing users’ activity in events on Twitter.

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Notes

  1. http://gti-ia.upv.es/sma/tools/magentix2/index.php.

  2. http://neo4j.com/.

  3. http://neo4j.com/developer/cypher-query-language/.

  4. http://gephi.org/gexf/format/.

  5. http://gephi.org/toolkit/.

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Acknowledgments

This work is partially supported by the PROMETEOII/2013/019, TIN2014-55206-R, TIN2015-65515-C4-1-R, H2020-ICT-2015-688095.

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Authors and Affiliations

  1. Universitat Politècnica de València, Valencia, Spain

    E. del Val, C. Martínez & V. Botti

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  1. E. del Val
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  2. C. Martínez
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  3. V. Botti
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Correspondence to E. del Val.

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Conflict of interest

Elena del Val, Carla Martinez, and Vicente Botti declare that they have no conflict of interest.

Ethical standard

This article does not contain any studies with human participants or animals performed by any of the authors. All the data used in the experiments were obtained from public datasets.

Additional information

Communicated by A. Herrero.

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del Val, E., Martínez, C. & Botti, V. Analyzing users’ activity in online social networks over time through a multi-agent framework. Soft Comput 20, 4331–4345 (2016). https://doi.org/10.1007/s00500-016-2301-0

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