Assessing library topics using sentiment analysis in R: a discussion and code sample

Abstract

This article discusses the use of R programing language for executing a sentiment analysis of tweets pertaining to library topics. This discussion is situated within the literature of marketing and management sciences, which is employing methods of machine learning and business intelligence to make informed decision-making, and library administration, which has expressed great interest in social media engagement within its literature but has yet to adopt these types of analysis. Presented in this article is a sample code with instructions on how users may execute it within R to retrieve and analyze tweets relevant to library services. Two examples created using the code (analysis of top librarians’ tweets and analysis of posts about major book publishers) are used to demonstrate the functionality of the code. The code presented in this article may be used by libraries to analyze tweets about their library and library-related topics, which, in turn, may inform management and marketing design.

Keywords:

• Data visualization
• library services
• sentiment analysis
• Twitter

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Notes on contributors

Brady D. Lund

Brady Lund is a PhD student at Emporia State University’s School of Library and Information Management. His research interests include human information behavior, informetrics, social informatics, and library services to special populations.