Social network sites (SNSs) such as Facebook open up novel communication and marketing capabilities by engaging customers and other organizational stakeholders. This study applies insights from Social Information Processing theory to quantitatively characterize five measures of user engagement on SNSs: likes, comments and shares, and two chronemic (time-related) measures of response time and of the rate of comments. We use data collected unobtrusively from 939 posts on Facebook pages of seven organizations to describe the prevalence of the engagement activities, to measure the correlations between them, and to explore how engagement is influenced by post attributes. Findings demonstrate that, similarly to customer engagement behaviors in traditional settings, user engagement behaviors on SNSs too are rich and multifaceted, and are influenced by each organization's unique characteristics. The findings also suggest that engagement with a post can be predicted based on activity levels in the first hour after it is posted.
|Title of host publication
|Proceedings of the 49th Annual Hawaii International Conference on System Sciences, HICSS 2016
|Ralph H. Sprague, Tung X. Bui
|IEEE Computer Society
|Number of pages
|Published - 7 Mar 2016
|49th Annual Hawaii International Conference on System Sciences, HICSS 2016 - Koloa, United States
Duration: 5 Jan 2016 → 8 Jan 2016
|Proceedings of the Annual Hawaii International Conference on System Sciences
|49th Annual Hawaii International Conference on System Sciences, HICSS 2016
|5/01/16 → 8/01/16
Bibliographical notePublisher Copyright:
© 2016 IEEE.
- Online engagement
- Social information processing