Using HRG model to predict scientific impact

• PubRKD is now the front file that can run it all.
• Need to have ..tograph take an argument to know what the hell it does and how it works
• Working on procjson.py to process the data sets and output a time series tweet count for plotting
• grep 4808504820 procjson.tsv | wc -l there should be only one; the edge list needs to be redone

• http://www.clips.ua.ac.be/pattern
• Clustering
• Spectral signature
• Spectral Evolution
• Improving Twitter Retrieval by Exploiting Structural Information @inproceedings{luo2012improving, title={Improving Twitter Retrieval by Exploiting Structural Information}, author={Luo, Zhunchen and Osborne, Miles and Wang, Ting and others}, booktitle={Twenty-Sixth AAAI Conference on Artificial Intelligence}, year={2012} }

• Proc Apollo DS

• Proc Halyard DS

• Got tweets captured > tweets processed > tweets clustered > edgelist of usr citing clust

  • i can also list usr citing tweet;
  • [] Now I need to use the list of users and build a network from their users

• 22Mar16: Apollo DS tweets.json processed & can build a graph

  • need to add network metrics, connected components (etc.)
  • cluster tweets and plot users citing clusters & temporal signature
    • unsupervised, just give the tweets
  • build altmetric pub interest
  • develop a pub interest metric
  • HRG
  • done