Assessing symptoms of excessive sns usage based on user behavior and emotion: Analysis of data obtained by sns APIs

Ploypailin Intapong, Saromporn Charoenpit, Tiranee Achalakul, Michiko Ohkura

研究成果: Conference contribution

3 引用 (Scopus)

抜粋

The use of social networking sites (SNSs) continues to dramatically increase. People are spending unexpected and unprecedented amounts of time online. Excessive and compulsive use of them has been categorized as a behavioral addiction. This research is conducted to assess the symptoms of excessive SNS usage by studying user behavior and emotion in SNSs. We designed a data collection application and developed a tool for collecting data from questionnaires and SNSs by APIs. The data were collected at the Thai-Nichi Institute of Technology (TNI), Thailand from 177 volunteers. We introduce our analysis of data obtained by SNS APIs by focusing on Facebook and Twitter. We used modified IAT and BFAS to measure SNS addiction. The Facebook and Twitter results, including a combination with questionnaires, were analyzed to identify the factors associated with SNS addiction. Our analytic results identified potential candidates of the key components of SNS addiction.

元の言語English
ホスト出版物のタイトルSocial Computing and Social Media
ホスト出版物のサブタイトルHuman Behavior - 9th International Conference, SCSM 2017 Held as Part of HCI International 2017, Proceedings
出版者Springer Verlag
ページ71-83
ページ数13
10282 LNCS
ISBN(印刷物)9783319585581
DOI
出版物ステータスPublished - 2017
イベント9th International Conference on Social Computing and Social Media, SCSM 2017 held as part of the 19th International Conference on Human-Computer Interaction, HCI International 2017 - Vancouver, Canada
継続期間: 2017 7 92017 7 14

出版物シリーズ

名前Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
10282 LNCS
ISSN(印刷物)0302-9743
ISSN(電子版)1611-3349

Other

Other9th International Conference on Social Computing and Social Media, SCSM 2017 held as part of the 19th International Conference on Human-Computer Interaction, HCI International 2017
Canada
Vancouver
期間17/7/917/7/14

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • これを引用

    Intapong, P., Charoenpit, S., Achalakul, T., & Ohkura, M. (2017). Assessing symptoms of excessive sns usage based on user behavior and emotion: Analysis of data obtained by sns APIs. : Social Computing and Social Media: Human Behavior - 9th International Conference, SCSM 2017 Held as Part of HCI International 2017, Proceedings (巻 10282 LNCS, pp. 71-83). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); 巻数 10282 LNCS). Springer Verlag. https://doi.org/10.1007/978-3-319-58559-8_7