Abstract
This poster presents preliminary findings from a textual analysis of social media posts created by public libraries. We collected a text corpus, consisting of 3,622 Facebook posts containing more than seven words from 151 public libraries. We conducted a term frequency analysis and latent dirichlet allocation (LDA) topic modeling to explore the content of Facebook posts. The results revealed that terms related to library programming and library event announcements appeared frequently. The LDA topic modeling identified 25 topics underlying the corpus. We observed various topics were posted on public library Facebook Pages while library programming and event related topics were most common.
| Original language | English |
|---|---|
| Pages (from-to) | 718-719 |
| Number of pages | 2 |
| Journal | Proceedings of the Association for Information Science and Technology |
| Volume | 54 |
| Issue number | 1 |
| DOIs | |
| State | Published - Jan 2017 |
Bibliographical note
Publisher Copyright:Copyright © 2017 by Association for Information Science and Technology
Keywords
- LDA topic models
- public libraries
- social media
- textual analysis
ASJC Scopus subject areas
- General Computer Science
- Library and Information Sciences