Languages' impact on emotional classification methods

• Autorzy: Eilertsen Alexander C. , Højbjerg Rose Dennis , Langballe Erichsen Peter , Engesgaard Christensen Rasmus , Pratap Deb Nath Rudra

Identyfikatory

DOI

10.15439/2019F143

• Konferencja: Federated Conference on Computer Science and Information Systems (14 ; 01-04.09.2019 ; Leipzig, Germany)
• Języki publikacji: EN

Abstrakty

EN

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.

Słowa kluczowe

EN

sentiment analysis; emotional classification; text-to-emotion analysis; cross-language analysis; natural language processing

PL

analiza nastrojów; klasyfikacja emocjonalna; analiza międzyjęzykowa; przetwarzanie języka naturalnego

• Wydawca: Polskie Towarzystwo Informatyczne
• Czasopismo: Annals of Computer Science and Information Systems
• Rocznik: 2019
• Tom: Vol. 18
• Strony: 277--286
• Opis fizyczny: Bibliogr. 14 poz., rys., wz., tab.

Twórcy

autor

Eilertsen Alexander C.

• Department of Computer Science, Aalborg University, Selma Lagerløfs Vej 300, 9220 Aalborg Ø, Denmark

autor

Højbjerg Rose Dennis

• Department of Computer Science, Aalborg University, Selma Lagerløfs Vej 300, 9220 Aalborg Ø, Denmark

autor

Langballe Erichsen Peter

• Department of Computer Science, Aalborg University, Selma Lagerløfs Vej 300, 9220 Aalborg Ø, Denmark

autor

Engesgaard Christensen Rasmus

• Department of Computer Science, Aalborg University, Selma Lagerløfs Vej 300, 9220 Aalborg Ø, Denmark

autor

Pratap Deb Nath Rudra

• Department of Computer Science, Aalborg University, Selma Lagerløfs Vej 300, 9220 Aalborg Ø, Denmark

Bibliografia

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• 11. J. C. Platt, “Sequential minimal optimization: A fast algorithm for training support vector machines,” in Advances in Kernel Methods-Support Vector Learning, 1999.
• 12. T. Ho, “Random decision forests,” in Document Analysis and Recognition, International Conference on, vol. 1, 09 1995. http://dx.doi.org/10.1109/IC-DAR.1995.598994. ISBN 0-8186-7128-9 pp. 278 – 282 vol. 1.
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Uwagi

1. Track 2: Computer Science & Systems

2. Technical Session: 4th International Workshop on Language Technologies and Applications

3. Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2020).