A Prototype for Sentiment Analysis Using Big Data Tools View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2017-09-24

AUTHORS

Kusum Yadav , Siddharth Swarup Rautaray , Manjusha Pandey

ABSTRACT

The Big Data is referred to a massive accumulation of digital data generated in each and every second in structured, semi-structured and unstructured format throughout the world. The rising field of big data analytic has driven the researcher worldwide toward design, development and implementation of various tools, technologies, architecture and platforms for analyzing the huge volume of data generated day to day. Big data consist of data sets which is difficult for legacy database management system to analysis. This paper details some analysis like sentiment analysis, feedback analysis. Sentiment analysis also known as opinion mining, is a process of getting views of public from feedback or review. Opinion are central to almost all human activities because they are key influencer of our behavior. Sentiment analysis is the task of identifying positive, negative or even neutral opinion. Feedback is detail about reaction to a product, a person performance of a task, etc. that can be used as a basis for enhancement. Feedback are chief means for the system enrichment, finding ambiguities and as well as for proper work distribution. Feedback can be used as a tool to draw proper decision, it is important not only when it highlights weaknesses but also for strengths. Since the feedback can induce both positive and negative, it is mandate to be careful when drawing any conclusion as improper analysis can produce wrong results. As a result the enhancements done will also be wring in the new system. We will be implementing this proposed system for sentiment analysis using Map-Reduce framework for processing large data set and for storage we will use Hadoop. More... »

PAGES

103-117

Book

TITLE

Computational Intelligence, Communications, and Business Analytics

ISBN

978-981-10-6426-5
978-981-10-6427-2

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/978-981-10-6427-2_9

DOI

http://dx.doi.org/10.1007/978-981-10-6427-2_9

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1091909696


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