Prediction of Polysemous Words in Sentiment Analysis: A Review - Malik, Manisha; Verma, Neetu (International Journal of Computer Sciences and Engineering, 2020)
In the last some years, new methods of communication channels have appeared and become indifferent. These communication channels are the social networking sites which have experienced an exponential growth. During the translation or communication, the problem of polysemy may cause difficulties. Therefore, there is a dire need for sentiment analysis process which can automatically extract and detect the sentiments of data extracted from micro blogging sites. It requires efficient techniques to collect a large amount of social media data and extract meaningful information from them. This paper presents a document level lexicon-based approach to detect the sentiment polarity. So, we focused on preprocessing of data. Instead of removing all polysemy, it includes some polysemous words in the complete procedure of sentiment analysis. We use specific number of polysemy words there but in future we will focus on different words and enhance the accuracy of our documentation.