Languages' impact on emotional classification methods

Alexander C. Eilertsen, Dennis Hojbjerg Rose, Peter Langballe Erichsen, Rasmus Engesgaard Christensen, Rudra Pratap Deb Nath

Research output: Contribution to book/anthology/report/conference proceedingArticle in proceedingResearchpeer-review

Abstract

There is currently a lack of research concerning whether Emotional Classification (EC) research on a language is applicable to other languages. If this is the case then we can greatly reduce the amount of research needed for different languages. Therefore, we propose a framework to answer the following null hypothesis: The change in classification accuracy for Emotional Classification caused by changing a single preprocessor or classifier is independent of the target language within a significance level of p = 0.05. We test this hypothesis using an English and a Danish data set, and the classification algorithms: Support-Vector Machine, Naive Bayes, and Random Forest. From our statistical test, we got a p-value of 0.12852 and could therefore not reject our hypothesis. Thus, our hypothesis could still be true. More research is therefore needed within the field of cross-language EC in order to benefit EC for different languages.
Original languageEnglish
Title of host publicationProceedings of the 2019 Federated Conference on Computer Science and Information Systems, FedCSIS 2019
EditorsMaria Ganzha, Leszek Maciaszek, Leszek Maciaszek, Marcin Paprzycki
Number of pages10
PublisherIEEE
Publication dateSep 2019
Pages277-286
Article number8860017
ISBN (Electronic)9788395541605
DOIs
Publication statusPublished - Sep 2019
Event2019 Federated Conference on Computer Science and Information Systems, FedCSIS 2019 - Leipzig, Germany
Duration: 1 Sep 20194 Sep 2019

Conference

Conference2019 Federated Conference on Computer Science and Information Systems, FedCSIS 2019
CountryGermany
CityLeipzig
Period01/09/201904/09/2019
SponsorIntel
SeriesFederated Conference on Computer Science and Information Systems
Volume18
ISSN2300-5963

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Keywords

  • Cross-Language Analysis
  • Emotional Classification
  • Natural Language Processing
  • Sentiment Analysis
  • Text-to-Emotion Analysis

Cite this

Eilertsen, A. C., Rose, D. H., Erichsen, P. L., Christensen, R. E., & Nath, R. P. D. (2019). Languages' impact on emotional classification methods. In M. Ganzha, L. Maciaszek, L. Maciaszek, & M. Paprzycki (Eds.), Proceedings of the 2019 Federated Conference on Computer Science and Information Systems, FedCSIS 2019 (pp. 277-286). [8860017] IEEE. Federated Conference on Computer Science and Information Systems, Vol.. 18 https://doi.org/10.15439/2019F143