yelp-sna

Social Network Analysis with Yelp Academic Dataset

1. Dependencies

   • LIBMF
   • Snappy
   • Octave 3.8
   • Python-2.7
   • numpy-1.9
   • Hadoop
   • Pig Latin

2. Check out

   # Cloned from https://github.com/kevinmao/yelp-sna
   cd ~
   git clone https://github.com/kevinmao/yelp-sna
   cd yelp-sna
   

3. Download Yelp Dataset Challenge

   # download from http://www.yelp.com/dataset_challenge
   

4. Unzip Yelp data

   make xunzip
   

5. Transform JSON format Yelp data to TSV format

   make transform
   

6. Split Yelp reviews into training and test sets

   make split_review
   

7. Map graphs into integer IDs

   make user_keys
   make business_keys
   make user_user
   

8. Create user-business review data

   make ub_review
   

9. Extract MaxWcc

   make get_maxwcc
   

10. Create core datasets

    make core_review 
    make core_review_sample # sampling
    

11. Create similarity scores

    make ub_similarity 
    

12. Create top_n candidates on Hadoop

    make top_n 
    

13. Link prediction

    make link_cand_summary
    make predicted_topn
    

14. Create training data for matrix factorization, training and predicting

    make create_mf_data
    make mf_train
    make mf_predict
    

15. Create training data for matrix factorization, training and predicting

    make create_mf_data
    make mf_train
    make mf_predict
    

16. Link prediction for matrix factorization

    make top_n_mf
    make mf_predicted_tp
    

17. Combine link prediction results

    make precision_comb
    make combine
    

18. Create plots

    # degree distribution
    make degree_dist
    
    # graph statistical info
    make graph_info
    
    # precision, precision@n and recall 
    make octave_plot