Natural language processing of text customer ratings in the banking sector | Sciact

Natural language processing of text customer ratings in the banking sector Научная публикация

Конференция

IV Международная научная конференция MIP: Engineering-IV-2022: Модернизация, Инновации, Прогресс: Передовые технологии в материаловедении, машиностроении и автоматизации
12-30 апр. 2022 , г. Санкт-Петербург - Красноярск

Журнал

AIP Conference Proceedings
ISSN: 0094-243X

Вых. Данные

Год: 2024, Том: 3021, Номер: 1, Номер статьи : 050008, Страниц : 7 DOI: 10.1063/5.0193411

Авторы

Urasova Anna ¹ , Oshchepkov Andrei ¹ , Plotnikov Andrei ^1,2 , Borovyh Kristina ²

Организации

1	The Institute of economics The Ural branch of the Russian academy of sciences, Perm branch
2	Perm National Research Polytechnic University

The paper compares two approaches to the texts analysis of the online customer ratings. The first approach focuses on a simple statistical analysis of the mentioned words number in ratings with a score from 1 to 5. The second approach applies the Word2Vec algorithm for the text analysis. The first approach shows the most popular words found in ratings. The second approach illustrates non-obvious words that can also be useful in the textual analysis of customer ratings. As a result, the authors came to the following generalization. The first approach forms the latent factor, i.e., “professionalism” (associated with the interaction of clients with a staff). It is presented in ratings as a negative factor (“non-professionalism”). An "organizational" (associated with time and some actions) latent factor is formed on the basis of the second approach (Word2Vec).

Urasova A. , Oshchepkov A. , Plotnikov A. , Borovyh K.
Natural language processing of text customer ratings in the banking sector
AIP Conference Proceedings. 2024. V.3021. N1. 050008 :1-7. DOI: 10.1063/5.0193411 Scopus OpenAlex

Опубликована online:

29 мар. 2024 г.

Scopus:	2-s2.0-85190574744
OpenAlex:	W4395093987

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