Review of the Lazada application on Google Play Store: sentiment analysis / Amyra Nur Ain Zulkifli and Nur Amalina Shafie - Zulkifli, Amyra Nur Ain; Shafie, Nur Amalina (UiTM Cawangan Perlis, 2024)
Sentiment analysis is a technique for gaining meaningful insight from unstructured and unorganized textual content from multiple platforms. It is a Natural Language Processing (NLP) method that may categorize data or reviews as positive, negative, or neutral. Analyzing reviews on the internet could yield helpful, actionable insights that could be economically beneficial to vendors or other interested parties. There are various online shopping platforms due to customer demand and rely on reviews and ratings while selecting choices. However, it could be difficult to tell whether the reviews are positive, negative, or both. The objective of this research is to classify the reviews on Lazada which is one of the online shopping platforms as positive, neutral or negative sentiments and to examine the words used most frequently in Lazada users’ reviews on the Google Play Store. This research used data from 7267 reviews that were extracted from the Google Play Store between 2019 and 2022 using the Google-play-scraper Python script. The reviews have been analyzed using the Valence Aware Dictionary and Sentiment Reasoner (VADER)’s to determine whether they are positive, neutral, or negative. The results indicate that 4229 reviews are positive. There are about 2857 negative sentiments and 181 neutral sentiments. It demonstrates that more people are happy using the Lazada app between 2019 and 2022. The results also demonstrate that sentiment analysis is an effective tool for categorising and evaluating other people's reviews and feedback.