International Research Journal of Engineering and Technology (IRJET)
e-ISSN: 2395-0056
Volume: 12 Issue: 03 | Mar 2025
p-ISSN: 2395-0072
www.irjet.net
Analyzing Sentiment in Social Media Communication and Its Effect on Mental Health Komal Sunil Jadhav1, Neha Arjun Nikam2, Riya Laxmikant Patil3, Ruchi Vipin Rane4 1Assistant Professor, Dept. of Information Technology & Computer Science, D.G. Ruparel College, Mumbai 2,3,4Students, Bsc Comp. Sci., D.G. Ruparel College, Mumbai, Maharashtra, India
---------------------------------------------------------------------***--------------------------------------------------------------------1.2 Social media Social media refers to digital platforms that allow users to sentiment analysis & its effects on the mental well-being of create and share content with their networks online. Popular communication through social media. Through analyzing the platforms like Facebook, Twitter, Instagram, Snapchat, responses gathered by a Google Form survey, tweets from WhatsApp and LinkedIn provide an easy way for users to Sentiment 140 data-set from Kaggle and real time tweets quickly share images, links, ideas and messages. However, retrieved via API’s applying NLP and logistic regression for the rise of social media has both positive and negative classification. User sentiments are classified as positive, impacts on mental health. neutral and negative, and evaluate their correlation to mental On the positive side, social media can foster a sense of health indicators. This research focuses on analyzing belonging and support through meaningful sentiment to provide a qualitative assessment of sentiment interactions. accuracy. On the other hand, negative experiences such as cyberbullying, social comparison, and online Key Words: Sentiment Analysis, Social Media, Mental harassment can contribute to mental health issues like Health, Emotion Detection, Online Communication depression and anxiety.
Abstract - This paper investigates the psychology of
1. INTRODUCTION
1.3 Sentiment Analysis Sentiment Analysis also known as opinion mining, is the systematic methodology of using natural language processing, machine learning and computational techniques to identify and extract the emotional tone or sentiment expressed in a piece of text. The objective is to identify whether the sentiment expressed in the text is positive, negative, or neutral.
1.1 Internet: The internet is a vast system of interconnected networks that enables users to access and exchange data, websites, services, and content from anywhere in the world. The internet has profoundly shaped modern life, becoming an essential source of news, entertainment, and education for people worldwide for over two decades. The internet has become an essential part of modern life, connecting people globally and enabling access to a wealth of resources.
2. Literature Review
A significant amount of research has been conducted in sentiment analysis, particularly within the fields of product reviews, movie reviews, and blogs. Several studies highlight the impact of social media sentiment on mental health. Research suggests that excessive exposure to negative content can increase psychological distress, while positive content enhances well-being. Sentiment analysis has been widely applied in fields such as marketing, politics, and health, making it a valuable tool for understanding emotional trends in social media interactions. This study builds upon existing research by examining real-world responses and their mental health implications.
3. Methods & Materials By analysing the responses collected from a Google Form survey, tweets from the Sentiment 140 dataset on Kaggle and real-time tweets retrieved via APIs, this study applies Natural Language Processing and logistic regression for sentiment classification. User sentiments are categorized as positive, neutral, or negative, and their correlation with mental health indicators is evaluated. The research aims to
fig.1: communication in the age of social media using Internet
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