Hi! Welcome to Twitter Social Analyzer!
The main goal of the project is to analyze different tweets about a concrete topic and generate a sentiment analysis about it using NLP tools.
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Project.
Twitter Social Analyzer comes up as a personal project that aspires to define a useful and simple tool to extract sentiments about a certain topic on Twitter social media. It also wants to get (if possible) Wikipedia definition about that topic.
For an easy use, it defines a simple GUI using Kivy for that purpose. The project is designed to contain all the different information and elements into differente and intuitive windows for a simple but comfortable experience.
The main tools used are:
- Tweepy for tweets parsing.
- urllib and BeautifulSoup for Wikipedia info extraction.
- matplotlib for graph plots.
- TextBlob for polarity and subjectivity analysis.
- WordCloud for word cloud plot generation.
- Spacy for NLP over tweets text.
- Uses a Kivy GUI for an easy interface.
- Parses most relevant tweets about the topic.
- Generates a word cloud based on tweets about the topic.
- Generates a polarity-subjectivity plot.
- Generates a sentiment value bar plot.
- Generates a resume with stats from tweets.
Here you can view the official project 📚 docs and 📔 wiki with technical info about the project.
With Git.
git clone https://github.com/Carlosma7/Twitter-Social-Analyzer.git
With GitHub CLI.
gh repo clone Carlosma7/Twitter-Social-Analyzer
Without GitHub.
wget https://github.com/carlosma7/Twitter-Social-Analyzer/archive/main.zip
To install all dependencies just execute:
pip3 install -r requirements.txt
To execute the program, after the requirements have been installed and the project downloaded, the following command is executed:
invoke execute
To clean the cache you can use:
invoke clean
Twitter Social Analyzer is an open source project that is open for new contributions if you want to. To contribute to the project you can contact me or just open a new pull request. Thanks in advance!
Carlos Morales Aguilera
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