Comparative Sentimental Analysis of Indian Politics using Twitter Dataset |
Author(s): |
| Patel Drashti A , Kalol Institute of Technology and Research Centre; Shilpa Patel, Kalol Institute of Technology and Research Centre |
Keywords: |
| Data Mining, Dictionary Approach, N - Gram, Naive Bayes (NB), Noun Phrase Sentimental Analysis, Term Frequency - Inverse Document Frequency (TF – IDF) |
Abstract |
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Use of Social media has been increased at its top now a day. Most of countries have so many social media users. So there is large amount of data collected in social media that re - present thoughts of people. Twitter is well known Social Media website that collects too much tweets during the day from various parts of the country. This collected data can be boon in Research field. Using NLP, statistics, or machine learning methods to extract, identify, or otherwise characterize the sentiment content of a text unit is called Sentimental Analysis. Sentimental Analysis is also called opinion mining. This data is very useful to decide the trend or current situations etc. We are going to research over Twitter Dataset for Political and Social Research Purposes. We will analyze the tweets and find outs user trends toward political decision and various problems of the country. |
Other Details |
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Paper ID: IJSRDV6I21792 Published in: Volume : 6, Issue : 2 Publication Date: 01/05/2018 Page(s): 2979-2981 |
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