In the constantly growing blogosphere with no restrictions on form or topic, a number of writing styles and genres have emerged. Recognition and classification of these styles has become significant for information processing with an aim to improve blog search or sentiment mining. One of the main issues in this field is detection of informative and affective articles. However, such differentiation does not suffice today. In this paper we extend the differentiation and suggest a fine-grained set of subcategories for affective articles. We propose and evaluate a classification method employing novel lexical, morphological, lightweight syntactic and structural features of written text. The results show that our method outperforms the existing approaches.
Publié le : 2017-02-07
Classification:
Knowledge and Information Engineering,
Blog, information processing, writing style, web genre, classification, natural language processing
@article{cai3121,
author = {Martin Virik; Slovak University of Technology in Bratislava, Faculty of Informatics and Information Technologies and Marian Simko; Slovak University of Technology in Bratislava, Faculty of Informatics and Information Technologies and Maria Bielikova; Slovak University of Technology in Bratislava, Faculty of Informatics and Information Technologies},
title = {Blog Style Classification: Refining Affective Blogs},
journal = {Computing and Informatics},
volume = {35},
number = {4},
year = {2017},
language = {en},
url = {http://dml.mathdoc.fr/item/cai3121}
}
Martin Virik; Slovak University of Technology in Bratislava, Faculty of Informatics and Information Technologies; Marian Simko; Slovak University of Technology in Bratislava, Faculty of Informatics and Information Technologies; Maria Bielikova; Slovak University of Technology in Bratislava, Faculty of Informatics and Information Technologies. Blog Style Classification: Refining Affective Blogs. Computing and Informatics, Tome 35 (2017) no. 4, . http://gdmltest.u-ga.fr/item/cai3121/