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Назва: Sentiment analysis of the US and Ukrainian presidential speeches
Автори: Dilai, Marianna
Onukevych, Yuliya
Dilay, Iryna
Приналежність: Applied Linguistics Department, Lviv Polytechnic National University
Lviv, Ukraine
Бібліографічний опис: Dilai M. Sentiment analysis of the US and Ukrainian presidential speeches / Marianna Dilai, Yuliya Onukevych, Iryna Dilay // Computational linguistics and intelligent systems, 25-27 June 2018. — Lviv : Lviv Polytechnic National University, 2018. — Vol 2 : Workshop. — P. 60–70. — (Part 1. Keynote speakers talks).
Bibliographic description: Dilai M. Sentiment analysis of the US and Ukrainian presidential speeches / Marianna Dilai, Yuliya Onukevych, Iryna Dilay // Computational linguistics and intelligent systems, 25-27 June 2018. — Lviv : Lviv Polytechnic National University, 2018. — Vol 2 : Workshop. — P. 60–70. — (Part 1. Keynote speakers talks).
Є частиною видання: Computational linguistics and intelligent systems (2), 2018
Дата публікації: 25-чер-2018
Видавництво: Lviv Polytechnic National University
Місце видання, проведення: Lviv
Часове охоплення: 25-27 June 2018
Теми: sentiment analysis
Ukrainian sentiment lexicon
manual annotation
presidential speeches
Кількість сторінок: 11
Діапазон сторінок: 60-70
Початкова сторінка: 60
Кінцева сторінка: 70
Короткий огляд (реферат): The paper presents the results of the sentiment analysis of the US and Ukrainian presidential speeches. By means of SentiStrength and UAM Corpus Tool programs, we attempt to extract opinions and sentiments in the speeches of Donald Trump and Petro Poroshenko. The main contribution of this study is the adaptation of the SentiStrength program to the Ukrainian language by compiling a political domain glossary of the Ukrainian emotion-bearing words. Furthermore, we compare lexical means of sentiment expression in the analyzed texts.
URI (Уніфікований ідентифікатор ресурсу): http://ena.lp.edu.ua:8080/handle/ntb/42572
ISSN: 2523-4013
Власник авторського права: © 2018 for the individual papers by the papers’ authors. Copying permitted only for private and academic purposes. This volume is published and copyrighted by its editors.
Перелік літератури: 1. G.E. Marcus, Emotions in politics, Annual Review of Political Science, 3, 2000, 221-50.
2. N. A. Valentino, T. Brader, E. W. Groenendyk, K. Gregorowicz & W. L. Hutchings, Election night’s alright for fighting: The role of emotions in political participation, Journal of Politics, 73, 2011, 156-170.
3. B. Albertson & S. K. Gadarian, Anxious Politics: Democratic Citizenship in a Threatening World, 2015, New York: Cambridge University Press,.
4. M. Lodge & C. Taber, Implicit affect for political candidates, parties, and issues: An experimental test of the hot cognition hypothesis, Political Psychology, 26, 2005, 455-482.
5. C. A. Smith & P.C. Ellsworth, Patterns of cognitive appraisal in emotion, Journal of Personality and Social Psychology, 48, 1985, 813-838.
6. B. Pang & L. Lee, Opinion mining and sentiment analysis, Foundations and Trends in Information Retrieval, Vol. 2, No 1-2 , 2008, 1–135.
7. B. Pang, L. Lee, S. Vaithyanathan, Thumbs up? Sentiment Classification using Machine Learning Techniques, Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing, Vol. 10, 2002,. 79–86.
8. E. Amigo, A. Corujo, J. Gonzalo, E. Meij, M. de Rijke, Overview of RepLab 2012: Evaluating Online Reputation Management Systems, CLEF 2012 Evaluation Labs and Workshop Notebook Papers, Rome.
9. B. Liu, Sentiment analysis and opinion mining, 2012, Morgan & Claypool Publishers.
10. L. Zhang, B. Liu, Aspect and Entity Extraction for Opinion Mining, in Data Mining and Knowledge Discovery for Big Data, 2014, Springer, Berlin, Heidelberg, 1–40.
11. M. Lobur, A. Romaniuk, M. Romanyshyn, Defining an approach for deep sentiment analysis of reviews in Ukrainian, Visnyk Natsionalnogo Universytetu Lvivska Politehnika, No 747, Komputerni systemy proektuvannia, Teoria i praktyka, 2012, 124–130.
12. M. Thelwall, K. Buckley, G. Paltoglou, D. Cai, & A. Kappas, Sentiment strength detection in short informal text, Journal of the American Society for Information Science and Technology, 61(12), 2012, 2544–2558.
References: 1. G.E. Marcus, Emotions in politics, Annual Review of Political Science, 3, 2000, 221-50.
2. N. A. Valentino, T. Brader, E. W. Groenendyk, K. Gregorowicz & W. L. Hutchings, Election night’s alright for fighting: The role of emotions in political participation, Journal of Politics, 73, 2011, 156-170.
3. B. Albertson & S. K. Gadarian, Anxious Politics: Democratic Citizenship in a Threatening World, 2015, New York: Cambridge University Press,.
4. M. Lodge & C. Taber, Implicit affect for political candidates, parties, and issues: An experimental test of the hot cognition hypothesis, Political Psychology, 26, 2005, 455-482.
5. C. A. Smith & P.C. Ellsworth, Patterns of cognitive appraisal in emotion, Journal of Personality and Social Psychology, 48, 1985, 813-838.
6. B. Pang & L. Lee, Opinion mining and sentiment analysis, Foundations and Trends in Information Retrieval, Vol. 2, No 1-2 , 2008, 1–135.
7. B. Pang, L. Lee, S. Vaithyanathan, Thumbs up? Sentiment Classification using Machine Learning Techniques, Proceedings of the ACL-02 Conference on Empirical Methods in Natural Language Processing, Vol. 10, 2002,. 79–86.
8. E. Amigo, A. Corujo, J. Gonzalo, E. Meij, M. de Rijke, Overview of RepLab 2012: Evaluating Online Reputation Management Systems, CLEF 2012 Evaluation Labs and Workshop Notebook Papers, Rome.
9. B. Liu, Sentiment analysis and opinion mining, 2012, Morgan & Claypool Publishers.
10. L. Zhang, B. Liu, Aspect and Entity Extraction for Opinion Mining, in Data Mining and Knowledge Discovery for Big Data, 2014, Springer, Berlin, Heidelberg, 1–40.
11. M. Lobur, A. Romaniuk, M. Romanyshyn, Defining an approach for deep sentiment analysis of reviews in Ukrainian, Visnyk Natsionalnogo Universytetu Lvivska Politehnika, No 747, Komputerni systemy proektuvannia, Teoria i praktyka, 2012, 124–130.
12. M. Thelwall, K. Buckley, G. Paltoglou, D. Cai, & A. Kappas, Sentiment strength detection in short informal text, Journal of the American Society for Information Science and Technology, 61(12), 2012, 2544–2558.
Тип вмісту : Conference Abstract
Розташовується у зібраннях:Computational linguistics and intelligent systems. – 2018 р.



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