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    R-Opitools – An Opinion Analytical Tool for Big Digital Text Document (DTD)

    Adepeju, Monsuru ORCID logoORCID: https://orcid.org/0000-0002-9006-4934 (2021) R-Opitools – An Opinion Analytical Tool for Big Digital Text Document (DTD). The Journal of Open Source Software, 6 (64). p. 3605.

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    Since the year 2000, various computational intelligence techniques have been developed for analyzing sentiments of users in the field of natural language processing (NLP). To date, the majority of the techniques as deployed across various fields, including social sciences (Ansari et al., 2020; Nikolovska & Ekblom, 2020; Somasundaran & Wiebe, 2010) and market research (Al-Otaibi et al., 2018; Feldman et al., 2011), have focused largely on detecting subjectivity, and/or extracting and classifying sentiments and opinions in a text document. Building on this existing work, the current paper advances an opinion impact analytical tool, named Opitools, that not only extracts inherent themes from within a digital text document (DTD), but also evaluates the extent to which a specified theme may have contributed to the overall opinions expressed by the document. Based on this advancement, Opitools has wider applications in the aforementioned application fields. For example, in law enforcement, the package can be deployed to understand factors (themes) that drive public perception of police services (Adepeju & Jimoh, 2021); and in product marketing, to identify factors that underlie customers satisfaction in a product.

    Impact and Reach


    Activity Overview
    6 month trend
    6 month trend

    Additional statistics for this dataset are available via IRStats2.


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