Predicting News Values from Headline Text and Emotions (CROSBI ID 660153)
Prilog sa skupa u zborniku | izvorni znanstveni rad | međunarodna recenzija
Podaci o odgovornosti
di Buono, Maria Pia ; Šnajder, Jan ; Dalbelo Bašić, Bojana ; Glavaš, Goran ; Tutek, Martin ; Milic-Frayling, Nataša
engleski
Predicting News Values from Headline Text and Emotions
We present a preliminary study on predicting news values from headline text and emotions. We perform a multivariate analysis on a dataset manually annotated with news values and emotions, discovering interesting correlations among them. We then train two competitive machine learning models – an SVM and a CNN – to predict news values from headline text and emotions as features. We find that, while both models yield a satisfactory performance, some news values are more difficult to detect than others, while some profit more from including emotion information.
machine learning, prediction, text classification, SVN, CNN, clustering, factorial analysis, news values
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Podaci o prilogu
1-6.
2017.
objavljeno
Podaci o matičnoj publikaciji
Proceedings of the 2017 EMNLP Workshop on Natural Language Processing Meets Journalism
Podaci o skupu
2017 EMNLP Workshop on Natural Language Processing Meets Journalism
predavanje
07.09.2017-11.09.2017
Kopenhagen, Danska