Sentiment Composition of Words with Opposing Polarities
Table 3: Performance of the automatic systems on SCL-OPP. Features used: unigrams (uni), part-of-speech of a unigram (POS), sentiment binary label of a unigram (sent. label), sentiment real-valued score of a unigram (sent. score), embeddings (emb). ‘emb(conc)’ is the concatenation of the embedding vectors of the constituent unigrams; ‘emb(avg)’ is the average vector of the unigram embeddings; ‘emb(max)’ is maximal vector of the unigram embeddings.
['[BOLD] Features', '[BOLD] Features', '[BOLD] Binary  [BOLD] (Acc.)', '[BOLD] Binary  [BOLD] (Acc.)', '[BOLD] Regression  [BOLD] (Pearson  [ITALIC] r)', '[BOLD] Regression  [BOLD] (Pearson  [ITALIC] r)']
The ‘majority label’, ‘last unigram’, ‘most polar unigram’, and ‘POS rule’ baselines are shown in rows a to d. Observe that the sentiment association of the last unigram is not very predictive of the phrase’s sentiment (row b). Both the ‘most polar unigram’ and the ‘POS rule’ classifiers perform markedly better than the majority baseline. Interestingly, the ‘most polar unigram’ classifier outperforms the slightly more sophisticated ‘POS rule’ approach on most tasks. Also, we found that within bigram phrases that contain adjectives or verbs, the adjective or verb constituents are the most polar words in only about half of the instances (and even less so in trigrams). This indicates that adjectives and verbs do not always dominate the sentiment in a phrase. Using only POS and binary sentiment labels of the constituent unigrams, the supervised learning algorithm does not perform much better than our ‘POS rule’ baseline (the accuracies in row e are just slightly higher than those in row d). With access to real-valued sentiment scores of unigrams much more accurate models can be learned (row f). Furthermore, the results show that the sentiment of a phrase depends on its constituent words and not only on the sentiment of the constituents (row g shows markedly better performance than row f; all the differences are statistically significant, p