Journal
BEHAVIOR RESEARCH METHODS
Volume 49, Issue 3, Pages 803-821Publisher
SPRINGER
DOI: 10.3758/s13428-016-0743-z
Keywords
Sentiment analysis; Affect detection; Opinion mining; Natural language processing; Automatic tools; Corpus linguistics
Categories
Funding
- Institute for Education Sciences (IES)
- National Science Foundation (NSF) [IES R305A080589, IES R305G20018-02, DRL-1418378]
- Division Of Research On Learning
- Direct For Education and Human Resources [1418352] Funding Source: National Science Foundation
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This study introduces the Sentiment Analysis and Cognition Engine (SEANCE), a freely available text analysis tool that is easy to use, works on most operating systems (Windows, Mac, Linux), is housed on a user's hard drive (as compared to being accessed via an Internet interface), allows for batch processing of text files, includes negation and part-of-speech (POS) features, and reports on thousands of lexical categories and 20 component scores related to sentiment, social cognition, and social order. In the study, we validated SEANCE by investigating whether its indices and related component scores can be used to classify positive and negative reviews in two well-known sentiment analysis test corpora. We contrasted the results of SEANCE with those from Linguistic Inquiry and Word Count (LIWC), a similar tool that is popular in sentiment analysis, but is pay-to-use and does not include negation or POS features. The results demonstrated that both the SEANCE indices and component scores outperformed LIWC on the categorization tasks.
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