Aspect-Based Sentiment Analysis of Russian Hotel Reviews
The paper presents an attempt to solve the task of aspect-based sentiment analysis in the domain of Russian-language hotel reviews, using distributed representation of words. The authors follow an approach similar to [Blinov, Kotelnikov, 2014], but applied to a different domain and using different parameters. The authors also present a new dataset that is made available to the community. To build the vector space of words with word2vec, a corpus comprising 50 329 hotel reviews was constructed. The next step was the compilation of aspect and sentiment lexicons in the vector space obtained. The lexicon construction approach was based on iteratively expanding a small set of initially specified terms. Finally, the sentiment of aspects in actual reviews was calculated given the aspect and sentiment terms found in the text and their weights, i.e. cosine similarity to the initial terms. The model was tested on a corpus of 6 876 texts from the same domain.