  Twitter has provided a great opportunity for public libraries to disseminate
information for a variety of purposes. Twitter data have been applied in
different domains such as health, politics, and history. There are thousands of
public libraries in the US, but no study has yet investigated the content of
their social media posts like tweets to find their interests. Moreover,
traditional content analysis of Twitter content is not an efficient task for
exploring thousands of tweets. Therefore, there is a need for automatic methods
to overcome the limitations of manual methods. This paper proposes a
computational approach to collecting and analyzing using Twitter Application
Programming Interfaces (API) and investigates more than 138,000 tweets from 48
US west coast libraries using topic modeling. We found 20 topics and assigned
them to five categories including public relations, book, event, training, and
social good. Our results show that the US west coast libraries are more
interested in using Twitter for public relations and book-related events. This
research has both practical and theoretical applications for libraries as well
as other organizations to explore social media actives of their customer and
themselves.
