Aspect-based Sentiment Analysis

Keras implementation (tensorflow backend) of aspect based sentiment analysis

Models

• Cabasc, WWW 2018
  Liu et al. "Content Attention Model for Aspect Based Sentiment Analysis"

• RAM, EMNLP 2017
  Chen et al. "Recurrent Attention Network on Memory for Aspect Sentiment Analysis"

• IAN, IJCAI 2017
  Ma ei al. "Interactive Attention Networks for Aspect-Level Sentiment Classification"

• MemNet, EMNLP 2016
  Tang et al. "Aspect Level Sentiment Classification with Deep Memory Network"

• ATAE-LSTM(AE-LSTM, AT-LSTM), EMNLP 2016
  Wang et al. "Attention-based LSTM for Aspect-level Sentiment Classification"

• TD-LSTM(TC-LSTM), COLING 2016
  Tang et al. "Effective LSTMs for Target-Dependent Sentiment Classification"

Preprocessing

1. Download pre-trained word embeddings here: glove.42B.300d.zip, unzip and put it in raw_data directory
2. Process raw data:

python3 process_raw.py

3. Prepare training, valid, testing data

python3 preprocessing.pt

Training

python3 train.py

Data Analysis

• Laptop

item	size
training set	2081
valid set	232
test set	638
word_vocab	3595
char_vocab	59
aspect	1181
aspect_text_word_vocab	981
aspect_text_char_vocab	45
word_max_len	83
< word_len = 0.98	54
word_left_max_len	70
< word_left_len = 0.975	34
word_right_max_len	78
< word_right_len = 0.985	39
char_max_len	465
< char_len = 0.98	255
char_left_max_len	365
< char_left_len = 0.98	177
char_right_max_len	400
< char_right_len = 0.981	177
aspect_text_word_max_len	8
< aspect_text_word_len = 0.99	6
aspect_text_char_max_len	58
< aspect_text_char_len = 0.99	28

• resturant(term)

item	size
training set	3241
valid set	361
test set	1120
word_vocab	4550
char_vocab	58
aspect	1528
aspect_text_word_vocab	1407
aspect_text_char_vocab	39
word_max_len	79
< word_len = 0.973	43
word_left_max_len	72
< word_left_len = 0.985	34
word_right_max_len	72
< word_right_len = 0.985	34
char_max_len	358
< char_len = 0.98	226
char_left_max_len	344
< char_left_len = 0.98	163
char_right_max_len	326
< char_right_len = 0.981	162
aspect_text_word_max_len	21
< aspect_text_word_len = 0.99	6
aspect_text_char_max_len	115
< aspect_text_char_len = 0.99	32

• resturant(category)

item	size
training set	3166
valid set	352
test set	973
word_vocab	5175
char_vocab	59
aspect	5
word_max_len	79
< word_len = 0.971	35
char_max_len	357
< char_len = 0.98	189

• twitter

item	size
training set	5623
valid set	625
test set	692
word_vocab	13522
char_vocab	116
aspect	118
aspect_text_word_vocab	176
aspect_text_char_vocab	30
word_max_len	73
< word_len = 0.997	37
word_left_max_len	39
< word_left_len = 0.985	28
word_right_max_len	67
< word_right_len = 0.994	32
char_max_len	188
< char_len = 0.985	151
char_left_max_len	156
< char_left_len = 0.98	125
char_right_max_len	164
< char_right_len = 0.981	138
aspect_text_word_max_len	3
< aspect_text_word_len = 0.99	2
aspect_text_char_max_len	21
< aspect_text_char_len = 0.99	16

Performance