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August 11, 2025JMET Journal of Management Entrepreneurship and Tourism

The Use of Machine Learning in Social Media Sentiment Analysis: Communication Strategies in The Digital Age

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Authors

NNNoviansyah NoviansyahBTBambang Krismono TriwijoyoNSNeny Sulistianingsih

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Overview

This analysis demonstrates how machine learning improves sentiment assessment on social media, indicating enhanced communication strategies.

Key Points

  • Machine learning provides faster and more accurate sentiment analysis compared to manual methods.
  • Analysis indicates effective sentiment classification into positive, negative, or neutral categories using algorithms like Support Vector Machine.
  • Case studies across major platforms like Twitter and Instagram highlight the utility of machine learning in mapping public opinion trends.
  • Integrating machine learning into communication strategies may enhance institutional connections with the public in a complex information landscape.

Cite This Study

Noviansyah et al. (2025) studied this question.

synapsesocial.com/papers/68c2354db210217d6476fccbhttps://doi.org/10.61277/jmet.v3i2.216
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1A Social Media Sentiment Analysis Using Machine Learning Approaches2025
  2. 2Consumer Behavior and Purchase Intentions: A Machine Learning-Based Sentiment Analysis of Social Media Data2024
  3. 3Efficiency Determination of Various Machine Learning Techniques for Sentiment Analysis on Social Media Platforms2025 · 3 citations
  4. 4Social Media Sentiment Analyzer using NLP2025
  5. 5The impact of social media on consumer choice2025