Real-time Insights from Social Media Data

Project information

The Real-Time Insights from Twitter project offers a comprehensive platform for monitoring and analyzing Twitter's dynamic conversations. By leveraging the Twitter API, this project facilitates the real-time collection, analysis, and visualization of tweets, providing valuable insights into public sentiment, trending topics, and other significant metrics.

Objectives:

Data Collection: The project uses the Tweepy library to stream tweets based on specific keywords, hashtags, or other criteria, capturing data that includes tweet content, user information, and metadata. Sentiment Analysis: By employing Natural Language Processing (NLP) tools like TextBlob, the project assesses the sentiment expressed in tweets, classifying them as positive, negative, or neutral. This helps in understanding public mood and opinion trends. Trend Identification: The project identifies and analyzes trending hashtags and topics, providing insights into what subjects are gaining traction or popularity over time. Visualization: Data analysis is further enhanced through visualizations using Matplotlib and Seaborn. These visual tools include time series plots, word clouds, and sentiment distribution charts, offering a clear view of trends and public discourse.

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