Lysander: Finding political journalists on Twitter
This directory contains software developed in the pilot of the project Automated Analysis of Online Behaviour on Social Media, a cooperation of the University of Groningen and the Netherlands eScience Center. The main project software repository is called machine learning.
The goal of the project is to analyze tweets of politicians and political journalists. Names of relevant politicians can be collected from documents like parliament member lists and ballots but it is much harder to find the names of relevant journalists. The software in this directory aims to find such journalists by examining the follower links between politicians and other users on Twitter.
python getFollowers.py markrutte sybrandbuma apechtold > getFollowers.out
to collect the people that are followed by the users in your seed list. The script needs your Twitter account data to be stored in a file definitions.py in the format:
# twitter.com authentication keys token = "???" token_secret = "???" consumer_key = "???" consumer_secret = "???"
Replace the strings "???" with the key information from https://apps.twitter.com , see https://www.slickremix.com/docs/how-to-get-api-keys-and-tokens-for-twitter/ for instructions
In order to find more relevant users, you can run this command after getFollowers.py is finished:
python makevec.py markrutte sybrandbuma apechtold < getFollowers.out > makevec.out 2> makevec.err
It generates a selection of relevant users (makevec.err) and a vector representations for these users (makevec.out)
Input data files for Dutch politicians can be requested from Erik Tjong Kim Sang e.tjong.kim.sang(at)esciencenter.nl