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| Content Provider | ACM Digital Library |
|---|---|
| Author | Ohkura, Michiko Intapong, Ploypailin Laohakangvalvit, Tipporn Achalakul, Tiranee |
| Abstract | The worldwide use of social networking sites (SNSs) continues to dramatically increase. People are spending unexpected and unprecedented amounts of time online. However, many studies have issued warnings about the negative consequences of excessive SNS usage, including the risk of addictive behavior. This research is conducted to detect the symptoms of excessive SNS use by studying user behaviors and emotions in SNSs. We employed questionnaires, SNS APIs, and biological signals as methods. The data obtained from the study will characterize SNS usage to detect excessive use. Finally, the analytic results will be applied for developing prevention strategies to increase the awareness of the risks of excessive SNS usage. . |
| Starting Page | 559 |
| Ending Page | 562 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781450345569 |
| DOI | 10.1145/2993148.2997620 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-10-31 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Social network addiction Sns Social networking sites User behavior |
| Content Type | Text |
| Resource Type | Article |
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