Prodigy InfoTech Internship: Sentiment Analysis on Social Media Data

Welcome to Task 04 of my Data Science Internship at Prodigy InfoTech!
This task focuses on applying sentiment analysis techniques to uncover public opinion from social media content.

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📌 Task Summary

Analyzed and visualized sentiment patterns in social media data to understand public opinion and attitudes towards specific topics, brands, or entities.
This task involved identifying sentiment polarity (positive, negative, neutral) from tweets or posts using natural language processing techniques.

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📊 Dataset

• Source: Twitter Entity Sentiment Analysis Dataset

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🧠 Skills & Concepts Applied

• Text preprocessing (tokenization, stopword removal, stemming)
• Sentiment classification using NLP techniques
• Data visualization for sentiment trends
• Exploratory Data Analysis (EDA)
• Word clouds and polarity graphs

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🛠 Tools & Libraries

• Python
• Pandas
• NLTK / TextBlob / VADER
• Matplotlib / Seaborn
• Scikit-learn (optional for model-based classification)

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📈 Outcome

Visual dashboards and metrics that illustrate how sentiments vary across tweets, brands, or events—helping to understand how people feel about particular topics.

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🙌 Let’s Connect

If you're interested in data science, NLP, or internship experiences, feel free to connect!

📬 Contact

• Email: mithildabhi898@gmail.com
• LinkedIn: Mithil Dabhi