Unveiling Emotional Landscape: A Sentiment Expedition Into Instagram Play Store And App Store Reviews Using Textblob

Résumé: Instagram is one of the most popular social media platforms that is now ruling over the netizens. This application has been downloaded from the Google Play Store for Android users and the App Store for iOS users. Every day thousands of reviews are posted on these two platforms by the users of Instagram. They review the application after using it and post it on the review section of the application page. On the other hand, TextBlob is one of the very new machine-learning Python libraries that is used to perform Natural Language Processing (NLP) tasks. Tokenization, POS-Tagging, word inflection, Noun phrase extraction, lemmatization, N-grams, and sentiment analysis are the most common examples of the NLP tasks that are implemented by using TextBlob. In this paper, we discussed about the execution of TextBlob in analyzing sentiment of the user of Instagram application from their reviews on Play Store and App Store. Moreover, a time phase model was executed which helped to predict the future of the application based on the user reviews. The sentiment analysis of the future has been done by it. The whole experiment goes through data preprocessing, finding out the sentiment of the users, implementing the time phase model, and predicting the future sentiment. It is a matter of fact that 93.27% accuracy was found when the predicted data was compared with the real data which is taken directly from the same sources.

Publié dans la revue: أطراس