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https://github.com/abhipatel35/twitter-analysis

Python script conducts sentiment analysis on Twitter data via GetOldTweets3, omitting NLTK. It preprocesses, analyzes sentiments, and visualizes results with a bar graph.
https://github.com/abhipatel35/twitter-analysis

emotion-recognition natural-language-processing nlp sentiment-analysis twitter twitter-analysis

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Python script conducts sentiment analysis on Twitter data via GetOldTweets3, omitting NLTK. It preprocesses, analyzes sentiments, and visualizes results with a bar graph.

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# Twitter-Analysis

This Python script retrieves tweets using the [GetOldTweets3](https://github.com/Mottl/GetOldTweets3) library and performs sentiment analysis on the gathered data.

## Overview

The script collects tweets posted between January 1, 2020, and April 1, 2020, using the specified search query. It then preprocesses the text data, cleans it by removing punctuations and stop words, and conducts sentiment analysis using a predefined sentiment lexicon.

## Technologies Used

- Python
- GetOldTweets3 Library
- Matplotlib Library

## Getting Started

To use this script:

1. Install the required libraries. You can install them via `pip`:

```bash
pip install GetOldTweets3 matplotlib
```

2. Clone the repository:

```bash
git clone https://github.com/abhipatel35/Twitter-Analysis.git
```

3. Run the script by executing:

```bash
python main.py
```

## Acknowledgments

The script utilizes the [GetOldTweets3](https://github.com/Mottl/GetOldTweets3) library by Mottl to access historical tweets based on specified search criteria.

## Results

The script generates a bar graph illustrating the sentiment distribution among the collected tweets. Additionally, the sentiment analysis results are printed to the console.

## File Structure

- `main.py`: Python script containing the code for data collection and sentiment analysis.
- `sentiments.txt`: File containing sentiment lexicon or word sentiment associations.
- `graph.png`: Generated bar graph showing the sentiment distribution among the tweets.

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