Exploring user engagement strategies and their impacts with social media mining: The case of public libraries

Zou, Hongbo, Chen, Hsuanwei Michelle, & Dey, Sharmistha (2015) Exploring user engagement strategies and their impacts with social media mining: The case of public libraries. Journal of Management Analytics, 2(4), pp. 295-313.

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Abstract

Public libraries are increasingly using social media to connect their users in innovative ways. Librarians make use of social media as a tool for ‘being part of their communities’, promoting library services and events, and creating participatory services. However, little empirical investigation has explored the success of such social media use by libraries. In this paper, we study the role of Twitter for engaging users via a focus on public libraries. We use topic-modeling techniques to classify library user engagement strategies into four categories: literature exhibits, engaging topics, community building and library showcasing.

These four engagement strategies are re-examined via a sentiment analysis of tweets collected from 10 public libraries over 3 months. Through data mining of tweets, we explore how user engagement strategies are used by libraries on Twitter, and suggest the best practices for libraries interested in pursuing social media initiatives to use to engage their users effectively.

Impact and interest:

Citation counts are sourced monthly from Scopus and Web of Science® citation databases.

These databases contain citations from different subsets of available publications and different time periods and thus the citation count from each is usually different. Some works are not in either database and no count is displayed. Scopus includes citations from articles published in 1996 onwards, and Web of Science® generally from 1980 onwards.

Citations counts from the Google Scholar™ indexing service can be viewed at the linked Google Scholar™ search.

ID Code: 97544
Item Type: Journal Article
Refereed: Yes
Additional Information: Special Issue: Big Data Methods and Applications
Keywords: big data analytics, user engagement, social media, social media mining, topic modelling, sentiment analysis, participatory services
DOI: 10.1080/23270012.2015.1100969
ISSN: 2327-0012
Divisions: Current > Schools > School of Information Systems
Current > QUT Faculties and Divisions > Science & Engineering Faculty
Copyright Owner: Copyright 2015 Taylor & Francis Group
Deposited On: 20 Jul 2016 23:23
Last Modified: 21 Jul 2016 21:50

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