Himanshu Jain

Work place: Vellore Institute of Technology, Vellore-632014, India

E-mail: himanshujain638@gmail.com


Research Interests: Mathematical Analysis


Himanshu Jain (born 2nd October, 1991) is a student of Master of Computer Applications in V.I.T. University, Vellore, India. He completed his BCA from University of Rajasthan, Jaipur in 2012 and then did a diploma In Hardware and Networking. He worked as an intern in a startup (Jan – Apr, 2016) named Sentilyze, focusing on the field of Sentimental analysis.

Author Articles
A Web Based Application for Sentiment Analysis

By Himanshu Jain

DOI: https://doi.org/10.5815/ijeme.2017.01.03, Pub. Date: 8 Jan. 2017

Sentiment analysis, also known as opinion mining, is referred to the studying and analyzing of people's opinions, emotions, sentiments, appraisals, evaluations and attitudes about an entity like an organization, product, service, issue, individual, event, topic, etc. and about their properties. It denotes a major problem part. While in Technical industry, the name, sentiment analysis is generally used, but in academic institutions, both terms, 'sentimental analysis' and 'opinion mining' are frequently used. They, unitedly represent the unique field of study. The term 'sentiment analysis' was first appeared in (Nasukawa and Yi, 2003) probably, and the term opinion mining was first appeared in (Dave, Lawrence and Pennock, 2003). In spite of the previous researches on sentiments and opinions published earlier, they become more prominent after this date.
Opinion mining and its related fields, for example, estimations, feelings, assessments, and states of mind are the subjects of investigation of slant examination and sentiment mining. The commencement and quick development of the field agree with those of the online networking on the Web, e.g., audits, gathering dialogs, web journals, microblogs, Twitter, and interpersonal organizations, in light of the fact that without precedent for mankind's history, we have an enormous volume of stubborn information recorded in computerized frames. We are working on accessing data from various data sources available online, including the various social networking sites, blogs or forums available. By using the provided APIs (of the respective site) and the web crawler mechanism, we will generate the outcomes and use them as a representation for users. Users can access the data represented in the forms of graphs and charts to analyze the behavior of the public on a particular brand, topic, issue or product.

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