Assessing symptoms of excessive SNS usage based on user behavior: Identifying effective factors associated with addiction components

Ploypailin Intapong, Saromporn Charoenpit, Tiranee Achalakul, Michiko Ohkura

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Social Networking Sites (SNSs) have exploded as a type of popular communication, suggesting exponential appeal. Unfortunately, one reason for their rise is the potential of excessive usage, which leads to negative consequences that are associated with addiction. In this research, we assessed the symptoms of excessive SNS usage by studying user behavior in SNSs. We employed the modified Internet Addiction Test (IAT) and the modified Bergen Facebook Addiction Scale (BFAS) to reflect addictive behaviors. We previously developed a data collection application and experimentally collected data from undergraduates in Thailand. In this article, we clarify the factors associated with addiction components (e.g., salience, mood modification, tolerance, withdrawal, conflict, and relapse), which are reflected by the questions of IAT and BFAS. We analyzed questionnaire and Facebook data by various methods. Our analytic results identified the effective factors associated with addiction components. Then we employed the Support Vector Regression (SVR) for evaluation. The outcome of our research can be applied for developing prevention strategies to increase the awareness of excessive SNS usage.

Original languageEnglish
Title of host publicationProceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume I
Subtitle of host publicationHealthcare Ergonomics
EditorsSebastiano Bagnara, Yushi Fujita, Riccardo Tartaglia, Sara Albolino, Thomas Alexander
PublisherSpringer Verlag
Pages394-406
Number of pages13
ISBN (Print)9783319960975
DOIs
Publication statusPublished - 2019 Jan 1
Event20th Congress of the International Ergonomics Association, IEA 2018 - Florence, Italy
Duration: 2018 Aug 262018 Aug 30

Publication series

NameAdvances in Intelligent Systems and Computing
Volume818
ISSN (Print)2194-5357

Other

Other20th Congress of the International Ergonomics Association, IEA 2018
CountryItaly
CityFlorence
Period18/8/2618/8/30

Keywords

  • Addiction components
  • SNS
  • SNS addiction
  • Social networking site

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Computer Science(all)

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  • Cite this

    Intapong, P., Charoenpit, S., Achalakul, T., & Ohkura, M. (2019). Assessing symptoms of excessive SNS usage based on user behavior: Identifying effective factors associated with addiction components. In S. Bagnara, Y. Fujita, R. Tartaglia, S. Albolino, & T. Alexander (Eds.), Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume I: Healthcare Ergonomics (pp. 394-406). (Advances in Intelligent Systems and Computing; Vol. 818). Springer Verlag. https://doi.org/10.1007/978-3-319-96098-2_50