International Journal of Scientific Development and Research - IJSDR
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Paper Title: Text Detection and Analyzing Sentiment Using Text Classification Approach
Authors Name: Ms. Mrunali D. Chaure , Prof. Jayant P. Mehare
Unique Id: IJSDR2008063
Published In: Volume 5 Issue 8, August-2020
Abstract: Text Classification, Text Mining and Sentiment Analysis have received huge attention, especially because of the availability of large volume of textual data on social media, e-commerce websites, blogs and other similar sources. This data is usually unstructured that becomes complex and expensive to extract knowledge from them to make some intelligent decisions. There is a growing need for developing different methodologies and models for efficiently processing the texts and extracting useful information from it. One way to extract information is text classification and its analysis that helps in decision making in various field of our lives. One of such a growing field is Social Media. This project performs the study and analysis of Social Media post by using different technique of text analysis and opinion mining along with sentiment analysis. This results in finding out the positive, negative users post and further analyzes negative category as violence, vulgar, offensive and hate on social media platform by performing text classification and analysis techniques.
Keywords: Decision Making, Natural Language Processing (NLP). Social Networking, Social Media, Text classification, Text Analysis, Unstructured Data.
Cite Article: "Text Detection and Analyzing Sentiment Using Text Classification Approach", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 8, page no.443 - 447, August-2020, Available :http://www.ijsdr.org/papers/IJSDR2008063.pdf
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Publication Details: Published Paper ID: IJSDR2008063
Registration ID:192279
Published In: Volume 5 Issue 8, August-2020
DOI (Digital Object Identifier):
Page No: 443 - 447
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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