The social media search system aims at providing an organized and integrated access and search support to a massive amount of unstructured, multilingual, user-generated content in an effective and efficient manner. Previous research on social media analytics mainly focuses on developing and applying advanced analysis methods and/or tools to make sense of the large amount of user-generated data over the Internet. Relatively little effort has been put to specifically examine the social media search system. In this study, we utilize and apply the DeLone and McLean IS Success Model to examine this type of systems. To do it, a lab experiment was conducted, and the results showed that all causal relationships, except for satisfaction to social benefit, specified in the DeLone and McLean IS Success Model hold in the context of the large-scale, social media search system. Specifically, we found that information quality and system quality associated with the system could significantly influence both users’ intention to use and satisfaction toward it, both of which, in turn, had significant impacts on users’ perceived individual benefit and social benefit. In addition, satisfaction could significantly influence intention to use the system.
Available at: https://aisel.aisnet.org/pajais/vol10/iss2/4/
Dang, Mandy Yan; Zhang, Gavin Yulei; and Chen, Hsinchun
"Adoption of Social Media Search Systems: An IS Success Model Perspective,"
Pacific Asia Journal of the Association for Information Systems: Vol. 10
, Article 4.
Available at: https://aisel.aisnet.org/pajais/vol10/iss2/4