Police message diffusion on Twitter: analysing the reach of social media communications

Social media are becoming increasingly important for communication between government organisations 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 analysed 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 customised 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 were combined with user characteristics in a multilevel logistic general linear model. Our main results show that URLs or use of informal communication increases 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.