TEXT MINING FOR PUBLIC PERCEPTION ANALYSIS IN THE TELECOMMUNICATION COMPANIES IN RWANDA: CASE OF MTN RWANDA
Abstract
The utilization of social media platforms has become indispensable for a significant number of individuals as a means to articulate their viewpoints and emotions. Organizations are increasingly recognizing social media platforms as a crucial instrument for obtaining pertinent information pertaining to various subjects and policies. Social media has had a significant rise in global usage, with a multitude of individuals utilizing these platforms to express their viewpoints on various aspects of social life, legislation, and politics. Twitter is a widely utilized social media platform for individuals to voice their viewpoints. The significant rise in information dissemination on Twitter throughout the year has positioned it as a prominent data source and a preferred option for conducting research on customer opinions and sentiment analysis. MTN Rwanda Plc has employed the use of questionnaires as a means of conducting customer opinion surveys for about 24 years since its establishment in Rwanda. This study aligned with the MTN project aimed at facilitating MTN Rwanda's access to consumer sentiments regarding newly announced products and services. It achieves this by analyzing the polarity of customer tweets on MTN Rwanda's Twitter accounts. The study examined the Twitter tweets of MTN Rwanda with the aim of doing sentiment analysis. The objective was to extract subjective sentiments, emotions, and public audience thoughts and opinions. The findings served as input to the MTN Rwanda customer experience department. The researcher utilized natural language processing and text mining methodologies to analyze and evaluate the public perceptions and expectations of MTN Rwanda's Twitter popularity rate. This involved employing text mining and analytics techniques. The findings indicated that there is a prevailing positive public impression and sentiment towards the tweets of MTN Rwanda. Moreover, the artificial neural network classifier predicts that this good sentiment is likely to persist in the future. The practical applications of the study were also discussed. It was expected that the study findings would benefit bilingual business entities on a global scale.
Key Words: Text Mining; Text Analytics; Social Media; Sentiment Analysis
CITATION: Murwanashyaka, J. M., & Uwimana, A. (2023). Text mining for public perception analysis in the telecommunication companies in Rwanda: case of MTN Rwanda. The Strategic Journal of Business & Change Management, 10 (4), 1167 – 1174. http://dx.doi.org/10.61426/sjbcm.v10i4.2811
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DOI: http://dx.doi.org/10.61426/sjbcm.v10i4.2811
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