This project analyzes the sentiment of tweets related to the Adipurush movie using natural language processing techniques. The sentiment analysis is performed on a collection of tweets retrieved from Twitter.
The main goals of this project are:
- Collect tweets related to the Adipurush movie from Twitter.
- Preprocess and clean the text data for analysis.
- Perform sentiment analysis to determine whether tweets express positive, negative, or neutral sentiments.
- Visualize the sentiment distribution using graphs and charts.
- Data Collection
- Data Preprocessing
- Sentiment Analysis
- Results and Visualization
- Setup
- Usage
- Contributing
We collected tweets using the Twitter API related to the Adipurush movie. The tweets were gathered over a specific period and stored in a dataset for analysis.
Before performing sentiment analysis, the collected tweets underwent preprocessing steps including text cleaning, removing special characters, tokenization, and removing stopwords.
The sentiment analysis was conducted using pretrained Model.
The sentiment analysis results were visualized using various graphs and charts. These visualizations provide insights into the sentiment distribution among the collected tweets.
To replicate or explore this project, follow these steps:
- Clone this repository:
git clone https://github.com/tosifAN/Sentiment_Analysis.git - Install the required packages:
Mention on Notebook. - Open and run the Jupyter Notebook file.
- Run the data collection script to gather new tweets.
- Run the data preprocessing script to clean and preprocess the collected tweets.
- Open and run the sentiment analysis notebook to classify sentiments.
- Explore the results and visualizations.
Contributions are welcome! If you'd like to improve this project or add new features, feel free to submit pull requests.