Understanding library user engagement strategies through large-scale Twitter analysis

Zou, Hongbo, Chen, Hsuanwei Michelle, & Dey, Sharmistha (2015) Understanding library user engagement strategies through large-scale Twitter analysis. In IEEE First International Conference on Big Data Computing Service and Applications, 30 March-2 April 2015, Redwood City, CA.

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Public libraries are increasingly using social media to connect their users in an innovative way. Librarians make use of social media with the purpose of "being part of their communities", or promoting libraries' services and events. Social media has become a significant platform for libraries to create their own participatory services emphasizing engagement with users. However, there has been little empirical investigation into the success of social media use by libraries. In this paper, we study the role of a recently popular social media, Twitter, in engaging users with a focus on public libraries. We use topic-modeling techniques to classify the library user engagement strategies into four categories -- literature exhibits, engaging topic, community building, and library showcasing. These four engagement strategies are re-examined with the tweets collected from ten public libraries over three months. The tweets topic distribution of every library is discussed in the paper. Finally, the impacts of every strategy on user engagement have been evaluated by users feedback on every tweet. Through the data mining of public libraries' tweets, we aim to explore how user engagement strategies are used by the libraries on Twitter and suggest the best practices for libraries on social media initiatives to engage their users effectively.

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ID Code: 97546
Item Type: Conference Paper
Refereed: Yes
Additional URLs:
Keywords: Big Data, User Engagement, Social Media, Data Mining
DOI: 10.1109/BigDataService.2015.31
ISBN: 9781479981281
Divisions: Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
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Copyright Owner: Copyright 2016 IEEE
Deposited On: 20 Jul 2016 23:12
Last Modified: 11 Aug 2016 00:55

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