TY - GEN
T1 - Assessing symptoms of excessive SNS usage based on user behavior
T2 - 20th Congress of the International Ergonomics Association, IEA 2018
AU - Intapong, Ploypailin
AU - Charoenpit, Saromporn
AU - Achalakul, Tiranee
AU - Ohkura, Michiko
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2019.
PY - 2019
Y1 - 2019
N2 - 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.
AB - 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.
KW - Addiction components
KW - SNS
KW - SNS addiction
KW - Social networking site
UR - http://www.scopus.com/inward/record.url?scp=85051980280&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85051980280&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-96098-2_50
DO - 10.1007/978-3-319-96098-2_50
M3 - Conference contribution
AN - SCOPUS:85051980280
SN - 9783319960975
T3 - Advances in Intelligent Systems and Computing
SP - 394
EP - 406
BT - Proceedings of the 20th Congress of the International Ergonomics Association (IEA 2018) - Volume I
A2 - Bagnara, Sebastiano
A2 - Fujita, Yushi
A2 - Tartaglia, Riccardo
A2 - Albolino, Sara
A2 - Alexander, Thomas
PB - Springer Verlag
Y2 - 26 August 2018 through 30 August 2018
ER -