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Assessing Symptoms of Excessive SNS Usage Based on User Behavior and Emotion: Analysis of Log Data

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Advances in Affective and Pleasurable Design (AHFE 2017)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 585))

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Abstract

The use of social networking sites (SNSs) continues to dramatically increase. People are spending unexpected and unprecedented amounts of time online. Such excessive and compulsive use has been categorized as a behavioral addiction. We assessed the symptoms of excessive SNS usage by studying user behavior and emotion in SNSs. In previous studies, we developed a data collection application as a tool for collecting data from questionnaires and SNSs by APIs. We experimentally collected data from undergraduate students at the Thai-Nichi Institute of Technology (TNI), Thailand. To improve our data analysis, we employed web log data and analyzed, including the combination with questionnaires data to clarify SNS usage behaviors and the factors associated with SNS addiction. Our analytical results identified the variables that distinguish excessive users from normal users.

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Acknowledgements

We thank Dr. Thongchai Kaewkiriya, the Head of Information and Communication Center, Thai-Nichi Institute of Technology (TNI) for the web log data dataset. We also thank the TNI students who volunteered their web log data.

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Authors and Affiliations

  1. Graduate School of Engineering and Science, Shibaura Institute of Technology, 3-7-5 Toyosu, Koto-ku, Tokyo, 135-8548, Japan

    Ploypailin Intapong

  2. Faculty of Information Technology, Thai-Nichi Institute of Technology, 1771/1, Pattanakarn Road, Suan Luang, Bangkok, 10250, Thailand

    Saromporn Charoenpit

  3. Department of Computer Engineering, King Mongkut’s University of Technology Thonburi, 126 Pracha-Uthit Road, Bangmot, Thung-Khru, Bangkok, 10140, Thailand

    Tiranee Achalakul

  4. College of Engineering, Shibaura Institute of Technology, 3-7-5 Toyosu, Koto-ku, Tokyo, 135-8548, Japan

    Michiko Ohkura

Authors
  1. Ploypailin Intapong
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  2. Saromporn Charoenpit
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  3. Tiranee Achalakul
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  4. Michiko Ohkura
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Corresponding author

Correspondence to Ploypailin Intapong .

Editor information

Editors and Affiliations

  1. School of Industrial Design, Carleton University, Ottawa, Ontario, Canada

    WonJoon Chung

  2. Department of Industrial Design, University of Illinois at Urbana Champaign, Champaign, Illinois, USA

    Cliff Sungsoo Shin

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Intapong, P., Charoenpit, S., Achalakul, T., Ohkura, M. (2018). Assessing Symptoms of Excessive SNS Usage Based on User Behavior and Emotion: Analysis of Log Data. In: Chung, W., Shin, C. (eds) Advances in Affective and Pleasurable Design. AHFE 2017. Advances in Intelligent Systems and Computing, vol 585. Springer, Cham. https://doi.org/10.1007/978-3-319-60495-4_41

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  • DOI: https://doi.org/10.1007/978-3-319-60495-4_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-60494-7

  • Online ISBN: 978-3-319-60495-4

  • eBook Packages: EngineeringEngineering (R0)

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