Dinesh Rawat, Kalpana Rawat, Arti Sharma and Shefali
Background: EdTech startups are shaping the Indian education industry with the aim of making education truly interesting. The covid-19 pandemic has affected all businesses except EdTech sector. EdTech industry is among those sectors that has observed rapid growth during covid-19. EdTech startups has witnessed a flood of users, funding, and stakeholders like never before. All these reasons make EdTech an interesting topic to study. In order to know EdTech, this study makes an attempt to carry out sentiment analysis of customer reviews on apps of leading educational technology (EdTech) startups.
Purpose: The objective of this paper is to study the sentiments of people towards different EdTech startups in India. The objective is achieved by conducting sentiment analysis of app reviews of three leading EdTech startups operating in India.
Methods: The study uses qualitative research where descriptive research design is used. Data is collected in the form of consumer app reviews from google play store. Reviews were taken for last six months. Total sample of 750 reviews were taken in the study which include 300 reviews for Byju’s learning app, 220 reviews for Unacademy and 230 reviews for Physicswallah. Purposive sampling is applied in this study. Sentiment analysis techniques is applied with the help of Azure Machine Learning MS Excel add-in.
Results: The results of the study suggest that majority of users have negative sentiments towards Physicswallah app, Byju’s learning app, and Unacademy learner app.
Conclusions: The results of this study would be useful to predict people sentiment about Edtech startups apps. The findings of this study give information to management of Edtech startups about positive or negative opinions of their application users so that they can develop strategies exclusively. Further research can include greater number of reviews and also consider demographic data of the reviewers.
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| Periodicity | Biannually |
| Issue-1 | May |
| Issue-2 | November |
| ISSN Print | 2321-2217 |
| ISSN Online | 2321-2225 |
| RNI No. | CHAENG/2013/50088 |
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