W2VLDA: Almost Unsupervised System for Aspect Based Sentiment Analysis
Table 12: Impact of different polarity seeds words for the sentiment polarity classification.
['[BOLD] Polarity:{POSITIVE},{NEGATIVE}', '[BOLD] Aspects acc.', '[BOLD] Polarity acc.']
Analogously to the domain aspect seed words, we have performed some experiments with the polarity words. We have tested several combinations of seeds with opposed polarity: excellent - horrible, awesome - awful, etc. Even with seed words of less extreme polarity, like good - bad, the results are quite stable. We also test combining more than a single word for each polarity, and as the results table shows, combining the three seed words for each polarity achieves the best result. The standard deviation for all the experiment runs is just a 1.2% of the accuracy. Similarly to what was observed for the domain aspects, the polarity seed words do not seem to affect the domain aspect classification accuracy, with only a 1.2% on standard deviation for all the runs.