Dictionary Based Opinion Classifier and Sentiment Analyser of Social Media Data
DOI:
https://doi.org/10.61841/0hb4ez47Keywords:
Sentiment Analysis(SA), Opinion Mining(OM), Dictionary Based Approach, Social Media Data.Abstract
Sentiment analysis or opinion mining is a method of NLP that is, used by organizations to find and categorize the expressive nature behind a body of text, which are given by, their customers as reviews about their products and services. This is very popular research area, which uses latest techniques like machine learning (ML), deep learning (DL) and artificial intelligence (AI) to find the insights of user text for finding user sentiment and subjective information behind it.
The massive volume and variability of the data produced by online social media assistances various businesses in decisionmaking. This paper, explains a dictionary based approach to apply the sentiment analysis technique on twitter data. Real time user timeline tweets had extracted and stored as corpus. This corpus had used for determining user sentiment and opinion polarity. This paper also deals with the classification technique to classify the text into positive, negative or neutral based on the polarity value.
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