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Sentiment Analysis of Twitter Data

EasyChair Preprint no. 3422

5 pagesDate: May 17, 2020

Abstract

Social media have received more attention nowadays.

Public and private opinion about a wide variety of subjects are expressed and spread continually via numerous social media. Twitter is one of the social media that is gaining popularity. Twitter offers organizations a fast and effective way to analyze customers’ perspectives toward the critical to success in the market place. Developing a program for sentiment analysis is an approach to be used to computationally measure customers’ perceptions. This paper reports on the design of a sentiment analysis, extracting a vast amount of tweets. Prototyping is used in this development. Results classify customers’ perspective via tweets into positive and negative, which is represented in a pie chart and html page. However, the program has planned to develop on a web application system, but due to limitation of Django which can be worked on a Linux server or LAMP, for further this approach need to be done.

Keyphrases: NaturalLanguageProcessing, opnion Mining, Sentiment, Socialmedia, Twitter

BibTeX entry
BibTeX does not have the right entry for preprints. This is a hack for producing the correct reference:
@Booklet{EasyChair:3422,
  author = {Surbhi Singh and P. Padmanabhan},
  title = {Sentiment Analysis of Twitter Data},
  howpublished = {EasyChair Preprint no. 3422},

  year = {EasyChair, 2020}}
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