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Authors: Hodaya Uzan 1 ; Esther David 2 ; Moshe Koppel 3 and Maayan Geffet-Zhitomirsky 3

Affiliations: 1 Bar-ilan Univeristy, Israel ; 2 Ashkelon Academic College, Israel ; 3 Bar-ilan univeristy, Israel

Keyword(s): Politics Classifying, Machine Learning, Text Classification, Automatic Profiling, Facebook.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Industrial Applications of AI ; Soft Computing

Abstract: In this paper we consider automatic political tendency recognition in a variety of genres. To this end, four different types of texts in Hebrew with varying levels of political content (manifestly political, semipolitical, non-political) are examined. It is found that in each case, training and testing in the same genre yields strong results. More significantly, training on political texts yields classifiers sufficiently strong to classify non-political personal Facebook pages with fair accuracy. This suggests that individuals’ political tendencies can be identified without recourse to any tagged personal data.

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Paper citation in several formats:
Uzan, H.; David, E.; Koppel, M. and Geffet-Zhitomirsky, M. (2015). Automatic Political Profiling in Heterogeneous Corpora. In Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART; ISBN 978-989-758-074-1; ISSN 2184-433X, SciTePress, pages 476-481. DOI: 10.5220/0005270104760481

@conference{icaart15,
author={Hodaya Uzan. and Esther David. and Moshe Koppel. and Maayan Geffet{-}Zhitomirsky.},
title={Automatic Political Profiling in Heterogeneous Corpora},
booktitle={Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART},
year={2015},
pages={476-481},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005270104760481},
isbn={978-989-758-074-1},
issn={2184-433X},
}

TY - CONF

JO - Proceedings of the International Conference on Agents and Artificial Intelligence - Volume 1: ICAART
TI - Automatic Political Profiling in Heterogeneous Corpora
SN - 978-989-758-074-1
IS - 2184-433X
AU - Uzan, H.
AU - David, E.
AU - Koppel, M.
AU - Geffet-Zhitomirsky, M.
PY - 2015
SP - 476
EP - 481
DO - 10.5220/0005270104760481
PB - SciTePress

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