Abstract
Social media are becoming increasingly important for communication between government organizations and citizens. Although research on this issue is expanding, the structure of these new communication patterns is still poorly understood. This study contributes to our understanding of these new communication patterns by developing an explanatory model of message diffusion on social media. Messages from 964 Dutch police force twitter accounts are analyzed using trace data drawn from the Twitter™ API to explain why certain police tweets are forwarded and others are not. Based on an iterative human-calibration procedure, message topics were automatically coded based on customized lexicons. A principal component analysis of message characteristics generated four distinct patterns of use in (in)personal communication and new/versus reproduced content. Message characteristics where combined with user characteristics in a multilevel logistic general linear model. Our main results show that URLs or use of informal communication increase chances of message forwarding. In addition, contextual factors such as user characteristics impact diffusion probability. Recommendations are discussed for further research into authorship styles and their implications for social media message diffusion. For the police and other government practitioners, a list of recommendation about how to reach a larger number of citizens through social media communications is presented.
Original language | English |
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Pages (from-to) | 4-16 |
Number of pages | 13 |
Journal | Behaviour & Information Technology |
Volume | 34 |
Issue number | 1 |
DOIs | |
Publication status | Published - 26 Aug 2014 |
Research programs
- ESSB PA
- EUR ESSB 25