Sentiment Analysis of Twitter Data Using Naive Bayes Algorithm

Main Article Content

Vikas Malik, Amit Kumar


Sentiment analysis the process of computationally identifying and categorizing opinions expressed in a piece of text, especially in order to determine whether the writer’s attitude towards a particular topic, product, etc. is positive, negative, or neutral. Now a days the growth of social websites, blogging services and electronic media con-tributes huge amount of user give messages such as customer reviews, comments and opinions. Sentiment Analysis is an important term referred to collect information in a source by using NLP, computational linguistics and text analysis and to make decision by subjective information extracting and analyzing opinion, identifying positive and negative reviews measuring how positively and negatively an entity (public ,organization, product) is involved. Sentiment analysis is the area of study to analyze people’s reviews, emotion, attitudes and emotion from written languages. We concentrate on field of different opinion classification techniques, performed on any data set. Now a days most popular approaches are Bag of words and feature extraction used by researchers to deal with sentiment analysis i.e used by politician, news groups, manufactures organization, movies, products etc.

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How to Cite
, V. M. A. K. “Sentiment Analysis of Twitter Data Using Naive Bayes Algorithm”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 6, no. 4, Apr. 2018, pp. 120-5, doi:10.17762/ijritcc.v6i4.1530.