Title :
Understanding Library User Engagement Strategies through Large-Scale Twitter Analysis
Author :
Hongbo Zou ; Chen, Hsuanwei Michelle ; Dey, Sharmistha
Author_Institution :
Inf. Syst. Sch., Queensland Univ. of Technol., Brisbane, QLD, Australia
fDate :
March 30 2015-April 2 2015
Abstract :
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.
Keywords :
data mining; public libraries; social networking (online); data mining; large-scale Twitter analysis; library user engagement strategy; public libraries; social media; topic-modeling technique; Buildings; Communities; Libraries; Market research; Media; Twitter; Big Data; Data Mining; Social Media; User Engagement;
Conference_Titel :
Big Data Computing Service and Applications (BigDataService), 2015 IEEE First International Conference on
Conference_Location :
Redwood City, CA
DOI :
10.1109/BigDataService.2015.31