3rd Best Paper winner at the International Conference on Computational Linguistics and Intelligent Text Processing CICLing2015
The Repository includes the following :
- 33K Automatically annotated Reviews in Domains of Movies, Hotels, Restaurants and Products
- Domain specific lexicons, semi automatically generated from the datasets above (2K total)
- A total of 615 Experiments over each of the datasets experimenting :
- Classifiers : Linear SVM, Logistic Regression, KNN, BNB, SGD training with SVM (Hinge loss and L1 penality)
- Sandard Features : TFIDF, Term Count, Term Existence, Delta-TFIDF
- Lexicon Based Features: domain specific and domain general
- Combining features : Lexicon based feature vectors + Standard features
- Classification Problems : with neutral class included or not
- Balanced or unBalanced Datasets
- Results of Each of the Experiments
####ATT.csv
- Dataset of Attraction Reviews scrapped from TripAdvisor.com
- 2154 reviews
####HTL.csv
- Dataset of Hotel Reviews scrapped from TripAdvisor.com
- 15572 reviews
####MOV.csv
- Dataset of Movie Reviews scrapped from elcinema.com
- 1524 reviews
####PROD.csv
- Dataset of product reviews scrapped from souq.com
- 4272 reviews
####RES1.csv
- dataset of restaurant reviews scrapped from qaym.com
- 8364 reviews
####RES2.csv
- dataset of restaurant reviews scrapped from tripadvisor.com
- 2642 reviews
####RES.csv
- RES1.csv and RES2.csv combined
- 10970 reviews
Domain specific lexicons, semi automatically generated from the datasets above (2K total)
| lexicon | MOV | RES | PROD | HTL | BOOK | Total |
|---|---|---|---|---|---|---|
| size | 87 | 734 | 369 | 218 | 874 | 1913 |