Sentiment Analysis of Twitter Data

EasyChair Preprint 3422

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, Sentiment, Socialmedia, Twitter, opnion Mining

@booklet{EasyChair:3422,
  author    = {Surbhi Singh and P. Padmanabhan},
  title     = {Sentiment Analysis of Twitter Data},
  howpublished = {EasyChair Preprint 3422},
  year      = {EasyChair, 2020}}