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First, LIWC is not freely available (it costs a modest fee). However, it has several shortcomings with regard to usability and to the facile and broad measurements of its dictionaries. LIWC has proven extremely useful in a number of different disciplines and has had a large impact on our understanding of how lexical elements related to cognition, affect, and personal concerns can be used to better understand human behavior.
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The best-known example of an available sentiment analysis tool is Linguistic Inquiry and Word Count (LIWC), which comprises a number of dictionaries that capture conscious and unconscious psychological phenomena related to cognition, affect, and personal concerns. However, the freely available natural language processing (NLP) tools that measure linguistic features related to sentiment, cognition, and social order are limited. Measuring sentiment features automatically in a text is thus of value, to better understand how emotions, feelings, affect, and opinions influence cognition, economic choices, learner engagement, and political affiliation. The analysis of sentiment is an important component of a number of research disciplines, including psychology, education, sociology, business, political science, and economics. The results demonstrated that both the SEANCE indices and component scores outperformed LIWC on the categorization tasks. 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. 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. 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.