Sentiment Intensity Ranking among Adjectives Using Sentiment Bearing Word Embeddings
Raksha Sharma, Arpan Somani, Lakshya Kumar, Pushpak Bhattacharyya · 2017
Identification of intensity ordering among polar (positive or negative) words which have the same semantics can lead to a finegrained sentiment analysis.For example, master, seasoned and familiar point to different intensity levels, though they all convey the same meaning (semantics), i.e., expertise: having a good knowledge of.In this paper, we propose a semisupervised technique that uses sentiment bearing word embeddings to produce a continuous ranking among adjectives that share common semantics.Our system demonstrates a strong Spearman's rank correlation of 0.83 with the gold standard ranking.We show that sentiment bearing word embeddings facilitate a more accurate intensity ranking system than other standard word embeddings (word2vec and GloVe).Word2vec is the state-of-the-art for intensity ordering task.