TY - JOUR
T1 - Sentiment Analysis and Social Cognition Engine (SEANCE)
T2 - An automatic tool for sentiment, social cognition, and social-order analysis
AU - Crossley, Scott A.
AU - Kyle, Kristopher
AU - McNamara, Danielle
N1 - Funding Information:
This research was supported in part by the Institute for Education Sciences (IES) and the National Science Foundation (NSF) (Grant Nos. IES R305A080589, IES R305G20018-02, and DRL-1418378). The ideas expressed in this material are those of the authors and do not necessarily reflect the views of the IES or NSF.
Publisher Copyright:
© 2016, Psychonomic Society, Inc.
PY - 2017/6/1
Y1 - 2017/6/1
N2 - 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.
AB - 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.
KW - Affect detection
KW - Automatic tools
KW - Corpus linguistics
KW - Natural language processing
KW - Opinion mining
KW - Sentiment analysis
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U2 - 10.3758/s13428-016-0743-z
DO - 10.3758/s13428-016-0743-z
M3 - Article
C2 - 27193159
AN - SCOPUS:84969802865
SN - 1554-351X
VL - 49
SP - 803
EP - 821
JO - Behavior Research Methods
JF - Behavior Research Methods
IS - 3
ER -