publication . Preprint . 2018

Social Media Analysis For Organizations: Us Northeastern Public And State Libraries Case Study

Collins, Matthew; Karami, Amir;
Open Access English
  • Published: 24 Mar 2018
Social networking sites such as Twitter have provided a great opportunity for organizations such as public libraries to disseminate information for public relations purposes. However, there is a need to analyze vast amounts of social media data. This study presents a computational approach to explore the content of tweets posted by nine public libraries in the northeastern United States of America. In December 2017, this study extracted more than 19,000 tweets from the Twitter accounts of seven state libraries and two urban public libraries. Computational methods were applied to collect the tweets and discover meaningful themes. This paper shows how the librarie...
ACM Computing Classification System: InformationSystems_MISCELLANEOUS
free text keywords: Computer Science - Social and Information Networks, Computer Science - Computers and Society, Statistics - Applications, Statistics - Machine Learning
Download from
26 references, page 1 of 2

Aharony, N. (2010). Twitter Use in Libraries  : An Exploratory Analysis. Journal of Web Librarianship, 4(4), 333-350. [OpenAIRE]

Al-Daihani, S. M., & AlAwadhi, S. A. (2015). Exploring academic libraries ' use of Twitter  : a content analysis. The Electronic Library, 33(6), 1002-1015. [OpenAIRE]

American Libraries Association (ALA). (2014). State of America's Libraries Report 2014. Retrieved from

American Libraries Association (ALA). (2017). State of America's Libraries Report 2017. Retrieved from

Cain, J.O. (2017). Using Topic Modeling to Enhance Access to Library Digital Collections. Journal of Web Librarianship, (10)3, 210-225. Cavanagh, M. F. (2016). Micro-blogging practices in Canadian public libraries  : A national snapshot. Journal of Librarianship and Information Science, 48(3), 247-259.

Chew, C., & Eysenbach, G. (2010). Pandemics in the Age of Twitter  : Content Analysis of Tweets during the 2009 H1N1 Outbreak. PLoS ONE, 5(11), 1-13. [OpenAIRE]

Del Bosque, D., Leif, S. A., & Skarl, S. (2012). Libraries atwitter: trends in academic library tweeting. Reference Services Review, 40(2), 199-213.

Ghosh, D. (Debs), & Guha, R. (2014). What are we “tweeting” about obesity? Mapping tweets with Topic Modeling and Geographic Information System. Cartography and Geographic Information Science, (40)2, 90-102.

10. Guo, L., Vargo, C. J., Pan, Z., Ding, W., & Ishwar, P. (2016). Big Social Data Analytics in Journalism and Mass Communication  : Comparing Dictionary-Based Text Analysis and Unsupervised Topic Modeling. Journalism & Mass Communication Quarterly, 93(2), 332-359.

11. He, W., Zha, S., & Li, L. (2013). Social media competitive analysis and text mining  : A case study in the pizza industry. International Journal of Information Management, 33, 464-472.

12. Jamison-Powell, S., Linehan, C., Daley, L., Garbett, A., & Lawson, S. (2012). “I can't get no sleep”: Discussing #insomnia on Twitter. In Proceedings of the SIGCHI Conference on Human Factors in Computing Systems (pp. 1501- 1510). Retrieved from

13. Karami A. and Zhou L. (2014), Improving Static SMS Spam Detection by Using New Contentbased Features, Proceedings of the 20th Americas Conference on Information Systems (AMCIS), Savannah, GA.

14. Karami, A. (2015). Fuzzy topic modeling for medical corpora. University of Maryland, Baltimore County.

26 references, page 1 of 2
Powered by OpenAIRE Open Research Graph
Any information missing or wrong?Report an Issue