• A
  • A
  • A
  • ABC
  • ABC
  • ABC
  • А
  • А
  • А
  • А
  • А
Regular version of the site

Detection of Toxic Content in Russian Texts

Student: Nikita Barsukov

Supervisor: Alexander Omelchenko

Faculty: St. Petersburg School of Physics, Mathematics, and Computer Science

Educational Programme: Big Data Analysis for Business, Economy, and Society (Master)

Final Grade: 10

Year of Graduation: 2021

An aggressive behavior of users towards each other is a serious problem of many websites. It is impossible to manually track every message to prevent users from online harassment. Therefore, the automation of this process became the main goal of this work. The main steps of this paper were to build a Russian text classifier of toxic content and publish the solution to the open source. Deep learning methods were applied using Tensorflow library. FastText, multilingual Universal Sentence Encoder, Wiki40B and Navec models were used to get word embeddings. In order to classify the text, convolutional and recurrent neural network architectures were used. The best model achieved an accuracy of 91.43% on the test sample. The model with the best quality-to-memory ratio was published as a python package. Everybody can install it using the following command «pip3 install toxicity». The main aim was to make the product as easy to use as possible. To start using the package, it is not necessary to have knowledge in field of deep learning. It is enough to import the class constructor, create the instance, and call its method “predict”.

Full text (added May 17, 2021)

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