Twitter Sentiment Analysis: A Case Study of Ten University Libraries

Abstract

Sentiment analysis is a computer rule based automatic process that has the ability to scrutinize the short text message, user comments, and other textual information and gives the sentiment score on a given subject. The current study is to examine the sentiment analysis of twitter comments of ten university libraries. The ten of universities list was compiled from World university rankings 2019 (Time Higher Education Website). A total of 15850 number of tweets collected between 1st Jan 2013 and 1st September 2019 via Twitter Application Programming Interface (API) for further analysis. The study found overall av. Pos. - av. Neg. was 0.4115. Out 15850 tweets majority of the tweets from The Bodleian Libraries, University of Oxford about 2760 tweets and highest friend followers 76180 found. Significantly, The Bodleian Libraries, University of Oxford was the highest Av. Nos. of positive sentiment (1.7728). However, the lowest Av. Neg. sentiment received by Yale Library about (1.1454). Moreover, the study found that the word “exhibition” (499) times and “archive” (401) times used in total tweets. Likewise, the word “Congratulations” found average positive sentiment (3.0152) mentioned in total tweets. The study recommended that the library can use social networking sites and examine the user comments, feedback, and reviews that, a user had given on different posts. By doing this, the library will be in better position to overcome the problem and make better decisions for future.