For today’s #lunchtimePD exercise, I read:

Al-Daihani, S. and Abrahams, A., Analysis of Academic Libraries’ Facebook Posts: Text and Data Analytics. The Journal of Academic Librarianship, Vol 44, Issue 2 (2018).

A fascinating approach to LIS research, Al-Aihani and Abrahams used data and text-mining and sentiment analysis to analyse over 18,000 Facebook posts from the libraries of top ranked universities in the USA, UK, Canada and Australia. While the results weren’t necessarily surprising, they were insightful. The researchers found that the most engaging posts (with the most likes and comments) were those that had accompanying media content or photos. The most popular posts were about: animals, the library receiving accolades, new content from special collections and rare books, historical content, contests and the weather. I learned a lot just by reading about their analysis techniques and the tools that they used. This method could also be used for Twitter content analysis. Something to note though, this was a discussion of the data and findings but doesn’t draw inferences on how the data can inform best practices for academic libraries.


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