Twitter Sentiment Analysis
International Journal of Scientific Research in Computer Science Engineering and Information TechnologyPublished 3 June 2023Open access
Gunjan R. Patil, Rishiraj Shrivastava, Advin Manhar
Citations28
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TL;DR
The design of the sentiment analysis is reported on, rooting a vast quantum of tweets, and results classify guests' perspectives via tweets into positive and negative, which is represented in a Graph.
Abstract
Social media has entered further attention currently. Public and private opinions about a wide variety of subjects are expressed and spread continually via multitudinous social media. Twitter is one of the social media that's gaining trend. Twitter offers associations a fast and effective way to dissect guests ' perspectives toward the critical success in the request place. Developing a program for sentiment analysis is an approach to be used to computationally measure guests’ comprehension. This paper reports on the design of the sentiment analysis, rooting a vast quantum of tweets. Prototyping is used in this development. Results classify guests' perspectives via tweets into positive and negative, which is represented in a Graph. Still, the program has been planned to develop on a web operation system, but due to the limitation of Django which can be worked on a Linux Garcon or Beacon, further this approach needs to be done.
Keywords
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