Automating Analysis of User Review Texts

Student: Kashkarev Pavel

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Mathematical Methods of Modelling and Computer Technologies (Master)

Final Grade: 8

Year of Graduation: 2019

The paper is devoted to automating passenger car user comments in Internet (from the site auto.ru). To this end, I have developed software to download 35797 letters (in Russian) and present them as a user-friendly database. Also, I selected 111 keyword combinations to reflect car usage advantages or drawbacks. By applying the method of Annotated Suffix Tree, I obtained a 35797 x 111 of relevance indices between the keywords and comment texts. In this matrix, the entries related to car drawbacks are made negative. Application of the k-means clustering at experimentally determined K=9 leads to a very stable cluster structure. This structure admits a natural interpretation. In particular, there are 4 clusters related to various aspects to dynamics, comfort, etc. Distributions of car brands over the clusters are analyzed, too.

Full text (added May 18, 2019)

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