Sentiment in academic texts

Valery Solovyev, Marina Solnyshkina, Elzara Gafiyatova, Danielle McNamara, Vladimir Ivanov

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

The problem of sentiment analysis has been widely studied in the past several decades. The research in the area has been predominantly based on data collated from online messages, microblogs, reviews, etc. Significantly fewer studies have been conducted based on academic discourse and especially school textbooks. However, sentiment analysis of academic texts can help answer pressing issues relating the ways in which different referents are presented in contemporary Russian school textbooks. In this paper, we analyze the distribution of sentiment words and phrases in a Corpus of Russian school textbooks on History (Grades 10-11) and Social Sciences (Grades 5-11). The results of the study demonstrate that the discourse within (1) History textbooks used in the 10th and 11th grades of Russian schools and (2) Social Studies textbooks written by Nikitin for Russian schools (Grades 5-11) contains predominantly negative sentiment: The writers select negatively valenced words and prefer presenting negative referents. By contrast, the discourse within the set of Social Studies textbooks written by Bogolubov revealed a predominantly positive bias. The authors discuss the implications of these trends in relation to the potential impact of the tone of educational discourse on learning.

Original languageEnglish (US)
Title of host publicationProceedings of the 24th Conference of Open Innovations Association FRUCT, FRUCT 2019
PublisherIEEE Computer Society
Pages408-414
Number of pages7
ISBN (Electronic)9789526865386
DOIs
Publication statusPublished - May 9 2019
Event24th Conference of Open Innovations Association FRUCT, FRUCT 2019 - Moscow, Russian Federation
Duration: Apr 8 2019Apr 12 2019

Publication series

NameConference of Open Innovation Association, FRUCT
Volume2019-April
ISSN (Print)2305-7254

Conference

Conference24th Conference of Open Innovations Association FRUCT, FRUCT 2019
CountryRussian Federation
CityMoscow
Period4/8/194/12/19

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ASJC Scopus subject areas

  • Computer Science(all)
  • Electrical and Electronic Engineering

Cite this

Solovyev, V., Solnyshkina, M., Gafiyatova, E., McNamara, D., & Ivanov, V. (2019). Sentiment in academic texts. In Proceedings of the 24th Conference of Open Innovations Association FRUCT, FRUCT 2019 (pp. 408-414). [8711900] (Conference of Open Innovation Association, FRUCT; Vol. 2019-April). IEEE Computer Society. https://doi.org/10.23919/FRUCT.2019.8711900