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Authorship profiling without using topical information: Notebook for PAN at CLEF 2018
KTH, School of Electrical Engineering and Computer Science (EECS), Theoretical Computer Science, TCS. Gavagai, Stockholm, Sweden.ORCID iD: 0000-0003-4042-4919
2018 (English)In: CLEF 2018 Working Notes, CEUR-WS , 2018, Vol. 2125Conference paper, Published paper (Refereed)
Abstract [en]

This paper describes an experiment made for the PAN 2018 shared task on author profiling. The task is to distinguish female from male authors of microblog posts published on Twitter using no extraneous information except what is in the posts; this experiment focusses on using non-topical information from the posts, rather than gender differences in referential content.

Place, publisher, year, edition, pages
CEUR-WS , 2018. Vol. 2125
Series
CEUR Workshop Proceedings, ISSN 1613-0073 ; 2125
National Category
Gender Studies
Identifiers
URN: urn:nbn:se:kth:diva-234054Scopus ID: 2-s2.0-85051071094OAI: oai:DiVA.org:kth-234054DiVA, id: diva2:1245563
Conference
19th Working Notes of CLEF Conference and Labs of the Evaluation Forum, CLEF 2018, Avignon, France, 10 September 2018 through 14 September 2018
Funder
VINNOVA
Note

QC 20180905

Available from: 2018-09-05 Created: 2018-09-05 Last updated: 2018-09-05Bibliographically approved

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Karlgren, Jussi

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