Tracking and analysis on Twitter
Experts in digital forensics introduce Twitter Intelligence, open source intelligence (OSINT) project written in Python to carry out Twitter tracking and analysis tasks without using the Twitter API itself.
- This project is a Python 3.x application
- Package dependencies are in the requirements.txt file. Run the following command to install the dependencies:
pip3 install-r requirements.txt
- SQLite is used as the database
- Tweet data is stored in Tweet, User, Location, Hashtag, HashtagTweet tables
- The database is generated automatically, as experts in digital forensics report
- Ask for help
python3 tracking.py –h
- Get tweets by username
python3 tracking.py –username “HaberSau”
- Get tweets by query
python3 tracking.py –query “sakary
- Get tweet by specific date ranges
python3 tracking.py –username “HaberSau” –since 2015-09-10 –until 2015-09-12 –maxtweets 10
- If you get the tweet location, add the –location “True” parameter, but the application will slow due to the new response times
python3 tracking.py –query “sakarya” –location “True”
analysis.py performs analysis processing. According to specialists in digital forensics from the International Institute of Cyber Security, Twitter Intelligence performs user, hashtag and location analysis.
- Get help
python3 analysis.py –h
- Location analysis
python3 analysis py –location (The location analysis runs through the https://localhost:5000/locations address). You must write Google Map Api Keyat setting.py to display the map.
- Running hashtag analysis
python3 analysis.py –hashtag
- Running user analysis
python3 analysis.py –user
Working as a cyber security solutions architect, Alisa focuses on bug bounty and network security. Before joining us she held a cyber security researcher positions within a variety of cyber security start-ups. She also experience in different industry domains like finance, healthcare and consumer products.