W2VLDA: Almost Unsupervised System for Aspect Based Sentiment Analysis
Table 13: Results using misleading words as polarity seeds to check to which extent the sentiment polarity classification depends on the validity of the chosen polarity seeds.
['[BOLD] Polarity:{POSITIVE},{NEGATIVE}', '[BOLD] Aspects acc.', '[BOLD] Polarity acc.']
Finally, in order to perform a sanity check to evaluate if the sentiment polarity classification is really depending on the correct selection of the polarity seed words, we perform two more runs using misleading words as polarity seeds. In particular, we use cat and waitress for positives and dog and waiter for negatives. The use of these words as polarity seeds is obviously incorrect, and what we want to check is if using such meaningless words (for polarity) leads to bad polarity classification results.