Determination of the level of user perception through sentiment analysis studies in the context of marketing
DOI:
https://doi.org/10.17981/ingecuc.18.2.2022.19Keywords:
affective computing, perception level, opinion mining, polarity, sentiment analysisAbstract
Introduction: The comments made by the clients of the companies in the social networks and electronic commerce portals about products and services offered by them, not only allow the companies to determine the perception of the clients for decision making at the marketing level. They serve as a reference for other customers to make decisions before buying a product. One of the techniques derived from natural language processing and affective computing that allows determining the value of an opinion is sentiment analysis.
Objective: To determine a quantitative indicator of the level of perception through a mathematical equation that involves the polarity value (positive, negative, neutral) of an opinion.
Method: This work focused on the automation of the opinion mining process and the determination of the level of perception through the identification of the most used and suitable libraries for the development of this work; the identification of mathematical equations to determine the level of perception; the implementation of a tool to automate the process; and the verification of its usefulness through a case study.
Results: By means of a mathematical equation that involves the three polarities of an opinion, obtaining an automated tool in Python language, which makes use of the Paralleldots library.
Conclusions: The tool developed allows opinion mining studies to be carried out in which the added value is the estimation of a level of perception by opinion and in general. The proposed approach is intended to serve as a reference to be replicated and extrapolated in different application contexts in addition to marketing.
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