Journal
2018 4TH INTERNATIONAL CONFERENCE ON COMPUTING SCIENCES (ICCS)
Volume -, Issue -, Pages 166-174Publisher
IEEE
DOI: 10.1109/ICCS.2018.00035
Keywords
Social network; text mining; customer experience; sentiment analysis; opinion mining
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Corporations have always desired prompt customer experience feedback about their products for amending current pricing and policies to stay ahead of their competitors. A positive customer experience can be created by analyzing customer sentiments and acting on them promptly. Social networks like Twitter represent collective intelligence and opinion of the general public and hence can be harnessed for real-time feedback. They have evolved as a resource for extracting sentiments for applications in various fields. Sentiment analysis can be used to obtain the overall customer experience of a large customer base on a real time. In this research, a total of 153,651 distinct tweets for Twitter handle of 5 popular telecom brands in India: Aircel, Bharti Airtel, Idea Cellular, Reliance Jio and Vodafone India were extracted for five months to develop a prediction model for telecom subscriber addition using the sentiment score. The results were validated statistically using correlation analysis. Positive customer sentiments about the brand which they prefer is reflected by higher growth rate of new subscribers added with that brand in the study period. The sentiment analysis results can be used by managements to take timely actions for improving the future customer experience and avoiding customer churn.
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