Sentiment Analysis and Social Cognition Engine (SEANCE): An automatic tool for sentiment, social cognition, and social-order analysis.

Crossley, Scott A; Kyle, Kristopher; McNamara, Danielle S

Crossley, Scott A; Kyle, Kristopher; McNamara, Danielle S.

Afiliación

Crossley SA; Department of Applied Linguistics/ESL, Georgia State University, 25 Park Place, Suite 1500, Atlanta, GA, 30303, USA. scrossley@gsu.edu.
Kyle K; Department of Applied Linguistics/ESL, Georgia State University, 25 Park Place, Suite 1500, Atlanta, GA, 30303, USA.
McNamara DS; Department of Psychology, Learning Sciences Institute, Arizona State University, Tempe, AZ, USA.

Behav Res Methods ; 49(3): 803-821, 2017 06.

Article en En | MEDLINE | ID: mdl-27193159

RESUMEN

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.

Asunto(s)

Cognición; Minería de Datos; Emociones; Programas Informáticos; Humanos

Palabras clave

Affect detection; Automatic tools; Corpus linguistics; Natural language processing; Opinion mining; Sentiment analysis

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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Programas Informáticos / Cognición / Emociones / Minería de Datos Límite: Humans Idioma: En Revista: Behav Res Methods Asunto de la revista: CIENCIAS DO COMPORTAMENTO Año: 2017 Tipo del documento: Article País de afiliación: Estados Unidos Pais de publicación: Estados Unidos

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