Abstract
To help us go through the vast, multidisciplinary literature on game addiction, this study makes use of a knowledge extraction technique called Literature-Based Discovery (LBD) to identify potentially effective but under-studied measures that help prevent the negative effects of online game addiction among children and adolescents. LBD was implemented using association rule mining to generate a list of preventive measure-negative effect pairs (rules), which are then evaluated using the ‘support’ metric. This helped us identify preventive measures that have received relatively less research attention, and one such preventive measure is peer education. Using meta-analysis, we computed the average effect size of peer education and showed that it is comparable to other popular preventive measures in terms of effectiveness. This study which involves a total of 876 articles demonstrates generally that LBD can be a useful research method to discover promising but under-studied research topics in the existing literature.
Original language | English |
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Title of host publication | PACIS 2022 Proceedings |
Publisher | Association for Information Systems |
Number of pages | 16 |
Publication status | Published - Jul 2022 |
Event | Pacific Asia Conference on Information Systems (PACIS) 2022 - Virtual Conference Duration: 5 Jul 2022 → 9 Jul 2022 https://aisel.aisnet.org/pacis2022 |
Conference
Conference | Pacific Asia Conference on Information Systems (PACIS) 2022 |
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Abbreviated title | PACIS 2022 |
Period | 5/07/22 → 9/07/22 |
Internet address |
Keywords
- Literature-Based Discovery
- online game addiction
- preventive measures
- adolescents