Sentiment Analysis on Reviews of Agricultural Mobile Applications

Description

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Mude Sai Lakshmi¹, Gautam R. Parmar², and Amit Lathiya³ (ASPEE Agribusiness Management Institute, Navsari Agricultural University, Navsari, Gujarat^1,2 and Planning Cell, Directorate of Research and Dean PGS, Navsari Agricultural University, Navsari, Gujarat³)

Agriculture is a key sector in India for providing livelihood, as more than half of the population depends on agriculture. Farmers need timely and accurate information on farming activities but they are struggling to access this information, which affects the income of the country. Agricultural applications help farmers in getting information and supply of inputs on time. This study aimed to understand the present status of agricultural applications. A qualitative research design was used to achieve the objectives of the study. By using some keywords, agricultural apps data was gathered from the Google Play Store. The apps with a rating of 3.8 or higher and more than 10,000 downloads were selected. With the help of some keywords like mobile agriculture apps, best farm machinery applications, farm selling applications and frequently shared applications, reviews were gathered from 65 well-known mobile applications between January 2024 to September 2024. After collecting the data, NVivo 15 was used to analyze the sentiments. Sentiment analysis uses auto code feature for classifying reviews into positive and negative categories. If the reviews contain neither positive nor negative sentiments, they are identified as neutral. The results of the study would help service providers offer better services to customers by improving agricultural applications.