Twitter Scraper

Scrapes Twitter for data attached to a certain hashtag or user mention. Mentions in the tweet are saved to a database to be evaluated later. This is a tool for saving tweets related to certain hashtags, mentions, or phrases for data analysis later. Tweets are saved to a MongoDB and analysis of the tweets is left open to the user for their specific needs.

Installation

MongoDB and Databases

1. Install MongoDB, http://docs.mongodb.org/manual/installation/
2. Create dev_tweets and tweets databases and users

• mongo
• use dev_tweets

db.createUser(
              {
                user: 'twitterScraper', 
                pwd: 'twitterScraper', 
                roles: [ "readWrite", "dbAdmin" ]
              }
            )

• use tweets

db.createUser(
              {
                user: 'twitterScraper', 
                pwd: 'twitterScraper', 
                roles: [ "readWrite", "dbAdmin" ]
              }
            )

Project Setup

1. Clone project to your machine
2. Create a virtualenv for twitter-scraper
3. Start that virtualenv
4. pip install -r requirements.txt
5. Edit twitter-scraper.py
6. Enter your Twitter Application Keys, https://apps.twitter.com
7. Enter what you would like to be watching for on Twitter
8. Verify MongoDB users and database address
9. Save
10. Run python twitter-scraper.py

• For developer mode, to save to dev_tweets, run with -d true
• For verbose output to console run with -v true

Developing

Clone the repository and open a pull request to be merged back in.