Literature review on Real-time Location-Based Sentiment Analysis on Twitter

Authors

  • Dilmini Rathnayaka IT Demonstrator
  • Pubudu K.P.N Jayasena
  • Iraj Ratnayake

Abstract

Sentiment analysis mainly supports sorting out the polarity and provides valuable information with the use of raw data in social media platforms. Many fields like health, business, and security require real-time data analysis for instant decision-making situations.Since Twitter is considered a popular social media platform to collect data easily, this paper is considering data analysis methods of Twitter data, real-time Twitter data analysis based on geo-location. Twitter data classification and analysis can be done with the use of diverse algorithms and deciding the most appropriate algorithm for data analysis, can be accomplished by implementing and testing these diverse algorithms.This paper is discussing the major description of sentiment analysis, data collection methods, data pre-processing, feature extraction, and sentiment analysis methods related to Twitter data. Real-time data analysis arises as a major method of analyzing the data available online and the real-time Twitter data analysis process is described throughout this paper. Several methods of classifying the polarized Twitter data are discussed within the paper while depicting a proposed method of Twitter data analyzing algorithm. Location-based Twitter data analysis is another crucial aspect of sentiment analyses, that enables data sorting according to geo-location, and this paper describes the way of analyzing Twitter data based on geo-location. Further, a comparison about several sentiment analysis algorithms used by previous researchers has been reported and finally, a conclusion has been provided.

 

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Published

2021-08-31

How to Cite

Rathnayaka, D., Jayasena, P. K. ., & Ratnayake, I. . (2021). Literature review on Real-time Location-Based Sentiment Analysis on Twitter. Advances in Technology, 1(2), 393–418. Retrieved from https://journals.sjp.ac.lk/index.php/ait/article/view/4936

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Section

Data Science

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