Sentiment Analysis of Twitter Messages: Demonetization a Use Case

Kumar, Niharika

doi:10.1109/csitss.2017.8447796

Cited by 8 publications

(1 citation statement)

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“…Topic tracking involves identifying and analyzing trends in social media content related to specific topics or brands. Topic tracking can provide valuable insights into emerging issues or trends, which can help businesses take timely actions to address potential issues and improve their brand's reputation [7][8][9][10].…”

Section: Introductionmentioning

confidence: 99%

Real-Time Sentiment Analysis of Social Media Content for Brand Improvement and Topic Tracking

Barunaha,

Prakash,

Naresh

2023

Advances in Computer Science Research

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This research paper focuses on real-time sentiment analysis of social media content for brand improvement and topic tracking. With the advent of social media, customers can easily express their opinions and emotions about a brand or product. As a result, businesses need to monitor social media channels to understand their customers' sentiments and to make informed decisions that can improve their brand's reputation. This study aims to create a sentiment analysis system that can quickly and accurately determine the sentiment of social media content in real-time. The system classifies the sentiment of the text as good, negative, or neutral using natural language processing algorithms. Additionally, the research explores the use of topic modelling techniques to track trending topics and identify issues that may be affecting the brand's reputation. The system is tested on a large dataset of tweets related to various brands and topics. The outcomes show that the suggested method is capable of precisely determining the sentiment of social media content and monitoring trending topics. The research findings can provide valuable insights to businesses for brand improvement and to take timely actions to address any potential issues.

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Section: Introductionmentioning

confidence: 99%