Implicit Aspect Sentiment Analysis using WordNet for Twitter Social Media Review Identification
DOI:
https://doi.org/10.17762/msea.v71i4.1838Abstract
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%.