Online published on 3 December, 2019.
Text mining and sentiment analysis have recently received huge attention in recent year. Sentiment analysis is one of the major tasks of NLP. The data is usually unstructured and contains noise; therefore the task of gaining information is complex and expensive. There is a growing need for developing different methodologies and models for efficiently processing the texts and extracting information. One way to extract information is text mining and sentiment analysis. This paper provides an overview of different techniques used in text mining and sentiment analysis elaborating on all tasks. It also categorized at sentence level sentiment analysis and document level sentiment analysis.
Sentiment Analysis, Supervised Learning, Unsupervised Learning, Text Mining, Feature Extraction, Feature Representation