Using Machine Learning to Predict the Sentiment of Tweets Related to Artificial Intelligence in the Workplace

The rise of AI at work has led to many people sharing their thoughts on social media, mostly on Twitter. The research aims to study the use of machine learning to discover and forecast how people in professional environments feel about AI. There was a collection, preparation, and cleaning of a substantial dataset of AI-related tweets using natural language processing techniques. Among the tasks was cleaning the text, turning it into word tokens, and putting it in a format that machine learning can use. Support Vector Machine (SVM), Logistic Regression, and Random Forest were constructed and tested to check how accurately they could identify the sentiment polarity in a piece of content. That particular model performed well in distinguishing different sentiments from each other. It seems that people are divided in their opinion. although some users appreciate the possibilities brought by AI efficiency and new inventions, there are still concerns about job security and ethics. They can help inform business leaders and policy makers by making it clearer how people see the impact of automation and intelligent systems.

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Publication Details

Journal
International Journal of Scientific Development and Research
Published
2025-01-01
DOI
https://doi.org/10.56975/ijsdr.v10i5.302889
Primary Topic
Hate Speech and Cyberbullying Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

Using Machine Learning to Predict the Sentiment of Tweets Related to Artificial Intelligence in the Workplace

Tabrez Alam Khan, Shivani Gupta, Bushra Rehman
International Journal of Scientific Development and Research
Hate Speech and Cyberbullying Detection
article

Using Machine Learning to Predict the Sentiment of Tweets Related to Artificial Intelligence in the Workplace

Tabrez Alam Khan, Shivani Gupta, Bushra Rehman
article en

Abstract

The rise of AI at work has led to many people sharing their thoughts on social media, mostly on Twitter. The research aims to study the use of machine learning to discover and forecast how people in professional environments feel about AI. There was a collection, preparation, and cleaning of a substantial dataset of AI-related tweets using natural language processing techniques. Among the tasks was cleaning the text, turning it into word tokens, and putting it in a format that machine learning can use. Support Vector Machine (SVM), Logistic Regression, and Random Forest were constructed and tested to check how accurately they could identify the sentiment polarity in a piece of content. That particular model performed well in distinguishing different sentiments from each other. It seems that people are divided in their opinion. although some users appreciate the possibilities brought by AI efficiency and new inventions, there are still concerns about job security and ethics. They can help inform business leaders and policy makers by making it clearer how people see the impact of automation and intelligent systems.

International Journal of Scientific Development and ResearchVol. 10(5)
Lingaya's Vidyapeeth (IN)
Decent work and economic growth
Openalex Percentile: Top 95%
Hate Speech and Cyberbullying Detection
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