Sentiment Analysis for Web-based Big Data: A Survey
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Abstract
These days customers rely on the Web for the opinions on various products and services. Due to rapid increase of data availability in web, it is very difficult to manage these for an application. Again, these data are in heterogeneous formats as well as rapid changing in nature. Thus there is a need for an effective system to classify analyse web reviews as a big data analysis. This task of classifying and analyzing such collective web data together is known as opinion mining, and it is also known as sentiment analysis. Sentiment analysis is a very challenging and promising discipline which uses both intersection of information retrieval and computational linguistic techniques to deal with the reviews expressed in a source material. This work talks about the sentiment analysis process and focus on some machine learning techniques for sentiment classification and future challenges in opinion mining for big data.
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