/twitter_influence_metrics

REVEAL-REVEALing hidden concepts in Social Media @ NCSR Demokritos: Analyzing influence metrics in twitter

Primary LanguagePython

Twitter infuence metrics

@NCSR Demokritos

‘REVEAL-REVEALing hidden concepts in Social Media’ (Ε-11834) program, research and development in knowledge extraction from graphs representing Social Networks.

Exploring the concept of influence in a social media platform (Twitter). Investigation of simple metrics of influence, comparisons in terms of correlation. Presentation slides can be found here.

Instructions/How-to run

  1. edit Main.py file, replace paths and parameters as desired.
    Params: save : saves results into pickle files
    resultsFolder: folder path to save results, if desired
    dataset_path : location of dataset
    type :

    • simple : simple graph and centrality measures
    • local_networks: graph and local network subgraphs, running centralities on overall graph as well as local networks
    • weighted: creating weighted graph and running weighted centralities

  2. python Main.py to run