Comparing Sentence-Level Features for Authorship Analysis in Portuguese

• Type: Article in International Conference Proceedings Book
• Date: 2010

Authors

sousa-silva, r (Author) Other; sarmento, l (Author) Other; grant, t (Author) Other; oliveira, e (Author) FEUP; maia, b (Author) Other

Conference proceedings International

Title: COMPUTATIONAL PROCESSING OF THE PORTUGUESE LANGUAGE, PROCEEDINGS

Pages: 51-54

9th International Conference on Computational Processing of the Portuguese Language

Porto Alegre, BRAZIL, APR 27-30, 2010

Indexing

ISI Proceedings

ISI Web of Knowledge - 0 Citations

Scopus - 1 Citation

Scientific classification

FOS: Natural sciences > Computer and information sciences

CORDIS: Physical sciences > Computer science

Other information

Authenticus ID: P-005-5TW

DOI: 10.1007/978-3-642-12320-7_7

Abstract (EN): In this paper we compare the robustness of several types of stylistic markers to help discriminate authorship at sentence level. We train a SVM-based classifier using each set of features separately and perform sentence-level authorship analysis over corpus of editorials published in a Portuguese quality newspaper. Results show that features based on POS information, punctuation and word / sentence length contribute to a more robust sentence-level authorship analysis.

Language: English

Type (Professor's evaluation): Scientific

No. of pages: 4