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Analysis of topics in storytime books based on text mining: Preliminary findings
Author(s) -
Joo Soohyung,
Cahill Maria,
Ingram Erin
Publication year - 2020
Publication title -
proceedings of the association for information science and technology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.193
H-Index - 14
ISSN - 2373-9231
DOI - 10.1002/pra2.377
Subject(s) - subject (documents) , computer science , alphabet , term (time) , information retrieval , world wide web , library science , linguistics , philosophy , physics , quantum mechanics
This poster presents some preliminary findings from an on‐going study that explores the content of storytime books using text mining procedures. We analyzed 429 books recommended for public library storytime programs. For each, we collected two sources of text from the WorldCat database: abstracts and subject terms. Multiple textual analysis methods were employed, including term frequency, bi‐grams, term co‐occurrences, LDA topic modeling, and sentiment analysis. The preliminary findings identified different topics and genres covered in storytime books. The study found educational elements in storytime books, such as alphabet, numbers, and colors. In addition, books in storytimes involve various aspects of sentiment.