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http://dspace.dtu.ac.in:8080/jspui/handle/repository/18472| Title: | ANALYZING THE POLARITY & SUBJECTIVITY OF THE REAL TIME UNSTRUCTURED DATA USING NLP |
| Authors: | Gupta, Sumanyu |
| Keywords: | POLARITY SUBJECTIVITY REAL TIME UNSTRUCTURED DATA USING NLP |
| Issue Date: | 31-May-2021 |
| Description: | EXECUTIVE SUMMARY Sentiment analysis is a technique in tokenizing the phrases , sentences from a language to understand the content and emotions of an individuals. Regular language models are being used and turing machines has been trained in order for better results. It's research is based on text mining & social media content mining. Spread of its significance has covered almost all industries from software engineering to the executives sciences and sociologies to understand the societies movement and mode of interest.0 The technology has changed rapidly to bring in change from structured data understanding to unstructured data understanding in all the fields. The developing0estimation0examination0agrees0with0the0development0of0internet0based0 life,0for0example,0surveys,0gathering0conversations,0sites,0miniaturized0scale0web journals,0Twitter®0,0and0informal0communities.0Frameworks0are0being0applied0in0 pretty0much0every0business0and0social0area0since0sentiments0are0integral0to0all0 human0exercises0and0are0key0influencers0of0our0practices. Real time tweets are analyzed on various different areas for different users using Twitter® as a platform to calculate the polarity and the subjectivity of a text. Negative and positive sentiments of users regarding products and services on Twitter® platform was tracked and visualized to understand their sentiment towards it & their needs. Python is used to extract the data through Twitter® API and preprocess it further to bring insights and understand the users behavior. |
| URI: | http://dspace.dtu.ac.in:8080/jspui/handle/repository/18472 |
| Appears in Collections: | MBA |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| 22222K18_MBA_926.pdf | 1.38 MB | Adobe PDF | View/Open |
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