Sentiment Analysis on Anime-Series Reviews

Student: Elizaveta Severinova

Educational Programme: Philology (Bachelor)

Year of Graduation: 2023

This paper is devoted to the study of sentiment analysis on anime reviews of anime of different genres and different parts using the Dostoevsky Python library and semi-automated aspect extraction. 22330 reviews from Shikimori.me were automatically selected as initial data. The Dostoevsky model was pre-trained on a dataset of Russian posts from the VKontakte social network (RuSentiment) and allows to analyze the tone of other Internet texts. The paper contains the results of the analysis, which are the main trends in the positive or negative assessment of anime of different genres and parts, which made it possible not only to compare and count the polarities of reviews, but also to highlight particular positive and negative aspects - what the viewer pays attention to most often when writing reviews on anime.

Student Theses at HSE must be completed in accordance with the University Rules and regulations specified by each educational programme.

Summaries of all theses must be published and made freely available on the HSE website.

The full text of a thesis can be published in open access on the HSE website only if the authoring student (copyright holder) agrees, or, if the thesis was written by a team of students, if all the co-authors (copyright holders) agree. After a thesis is published on the HSE website, it obtains the status of an online publication.

Student theses are objects of copyright and their use is subject to limitations in accordance with the Russian Federation’s law on intellectual property.

In the event that a thesis is quoted or otherwise used, reference to the author’s name and the source of quotation is required.

Search all student theses