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Using Social Networks Data for Behavior and Sentiment Analysis

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Internet and Distributed Computing Systems (IDCS 2015)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 9258))

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Abstract

With the advent of social networks, a huge amount of information is generated and stored every day. The social networks therefore represent a potentially infinite source of user data, usable both for scientific and commercial applications. Specifically, they store a lot of data regarding the single individual and behavior, as well as information related to individuals and their relationship with other individuals, i.e. a sort of collective behavior. The combination of behavior and sentiment analysis tools with methodologies of affective computing could allow the extraction of useful data that convey information for different applications, such as detection of depression state in psychology, political events, stock marketing fluctuations. The paper surveys some data extraction tools for social networks and emerging computing trends such as behavior analysis, sentiment analysis and affective computing. Then the paper proposes a first architecture for behavior analysis integrating those tools.

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Authors and Affiliations

  1. Department of Medical and Surgical Sciences, Magna Græcia University Viale Europa, 88100, Catanzaro, Italy

    Barbara Calabrese, Mario Cannataro & Nicola Ielpo

Authors
  1. Barbara Calabrese
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  2. Mario Cannataro
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  3. Nicola Ielpo
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Corresponding author

Correspondence to Mario Cannataro .

Editor information

Editors and Affiliations

  1. School of Systems Engineering, University of Reading, Reading, Berkshire, United Kingdom

    Giuseppe Di Fatta

  2. Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica, University of Calabria Dipartimento di Ingegneria Informat, Rende, Italy

    Giancarlo Fortino

  3. School of Logistics and Engineer, University of Technology Wuhan, Wuhan, China

    Wenfeng Li

  4. CSIRO ICT, Acton, Australia

    Mukaddim Pathan

  5. School of Systems Engineering, University of Reading, Whiteknights, Reading, United Kingdom

    Frederic Stahl

  6. Dipartimento di Ingegneria Informatica, Modellistica, Elettronica e Sistemistica, University of Calabria, Rende, Italy

    Antonio Guerrieri

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© 2015 Springer International Publishing Switzerland

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Calabrese, B., Cannataro, M., Ielpo, N. (2015). Using Social Networks Data for Behavior and Sentiment Analysis. In: Di Fatta, G., Fortino, G., Li, W., Pathan, M., Stahl, F., Guerrieri, A. (eds) Internet and Distributed Computing Systems. IDCS 2015. Lecture Notes in Computer Science(), vol 9258. Springer, Cham. https://doi.org/10.1007/978-3-319-23237-9_25

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  • DOI: https://doi.org/10.1007/978-3-319-23237-9_25

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-23236-2

  • Online ISBN: 978-3-319-23237-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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