Implicit Aspect Sentiment Analysis using WordNet for Twitter Social Media Review Identification - Kale Santosh Shivnath, Sonawane Vijay Ramnath (Mathematical Statistician and Engineering Applications, 2022)
In this paper, we present an implicit sentiment analysis system for Twitter social media reviews based on the WordNet lexical database. The system uses WordNet to identify sentiment-bearing words, along with their associated sentiment aspects and polarities. Aspect sentiment detection is done using a rule-based approach, which is able to detect sentiment polarity for different aspects in a single review. The system is evaluated on a dataset containing 12,000 tweets and is shown to be able to achieve an accuracy of 82%.