On the author profiling and deception detection in Arabic shared task at FIRE

Francisco Rangel; Paolo Rosso; Anis Charfi; Wajdi Zaghouani; Bilal Ghanem; Javier Sánchez-Junquera

doi:10.1145/3368567.3368586

On the author profiling and deception detection in Arabic shared task at FIRE

Francisco Rangel
, Paolo Rosso
, Anis Charfi
, Wajdi Zaghouani
, Bilal Ghanem
, Javier Sánchez-Junquera

HBKU College of Humanities and Social Science

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

4 Citations (Scopus)

Abstract

This paper summarises the Author Profiling and Deception Detection in Arabic (APDA) shared task at PAN@FIRE 2019. Two have been the main aims of this year’s task: i) to profile the age, gender and native language of a Twitter user; ii) to determine whether an Arabic text is deceptive or not in two different genres: Twitter and news headlines. For this purpose we have created three corpora in Arabic. Altogether, the approaches of 13 participants are evaluated.

Original language	English
Title of host publication	FIRE 2019 - Proceedings of the 11th annual meeting of the Forum for Information Retrieval Evaluation
Editors	Prasenjit Majumder, Mandar Mitra, Surupendu Gangopadhyay, Parth Mehta
Publisher	Association for Computing Machinery
Pages	7-9
Number of pages	3
ISBN (Electronic)	9781450377508
DOIs	https://doi.org/10.1145/3368567.3368586
Publication status	Published - 12 Dec 2019
Event	11th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE 2019 - Kolkata, India Duration: 12 Dec 2019 → 15 Dec 2019

Publication series

Name	ACM International Conference Proceeding Series

Conference

Conference	11th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE 2019
Country/Territory	India
City	Kolkata
Period	12/12/19 → 15/12/19

Keywords

Arabic
Author profiling
Deception detection
FIRE
Twitter

Access to Document

10.1145/3368567.3368586

Cite this

Rangel, F., Rosso, P., Charfi, A., Zaghouani, W., Ghanem, B., & Sánchez-Junquera, J. (2019). On the author profiling and deception detection in Arabic shared task at FIRE. In P. Majumder, M. Mitra, S. Gangopadhyay, & P. Mehta (Eds.), FIRE 2019 - Proceedings of the 11th annual meeting of the Forum for Information Retrieval Evaluation (pp. 7-9). (ACM International Conference Proceeding Series). Association for Computing Machinery. https://doi.org/10.1145/3368567.3368586

Rangel, Francisco ; Rosso, Paolo ; Charfi, Anis et al. / On the author profiling and deception detection in Arabic shared task at FIRE. FIRE 2019 - Proceedings of the 11th annual meeting of the Forum for Information Retrieval Evaluation. editor / Prasenjit Majumder ; Mandar Mitra ; Surupendu Gangopadhyay ; Parth Mehta. Association for Computing Machinery, 2019. pp. 7-9 (ACM International Conference Proceeding Series).

@inproceedings{e730e5c3cb694532bb68695be0bb80ab,

title = "On the author profiling and deception detection in Arabic shared task at FIRE",

abstract = "This paper summarises the Author Profiling and Deception Detection in Arabic (APDA) shared task at PAN@FIRE 2019. Two have been the main aims of this year{\textquoteright}s task: i) to profile the age, gender and native language of a Twitter user; ii) to determine whether an Arabic text is deceptive or not in two different genres: Twitter and news headlines. For this purpose we have created three corpora in Arabic. Altogether, the approaches of 13 participants are evaluated.",

keywords = "Arabic, Author profiling, Deception detection, FIRE, Twitter",

author = "Francisco Rangel and Paolo Rosso and Anis Charfi and Wajdi Zaghouani and Bilal Ghanem and Javier S{\'a}nchez-Junquera",

note = "Publisher Copyright: {\textcopyright} 2019 Association for Computing Machinery.; 11th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE 2019 ; Conference date: 12-12-2019 Through 15-12-2019",

year = "2019",

month = dec,

day = "12",

doi = "10.1145/3368567.3368586",

language = "English",

series = "ACM International Conference Proceeding Series",

publisher = "Association for Computing Machinery",

pages = "7--9",

editor = "Prasenjit Majumder and Mandar Mitra and Surupendu Gangopadhyay and Parth Mehta",

booktitle = "FIRE 2019 - Proceedings of the 11th annual meeting of the Forum for Information Retrieval Evaluation",

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}

Rangel, F, Rosso, P, Charfi, A, Zaghouani, W, Ghanem, B & Sánchez-Junquera, J 2019, On the author profiling and deception detection in Arabic shared task at FIRE. in P Majumder, M Mitra, S Gangopadhyay & P Mehta (eds), FIRE 2019 - Proceedings of the 11th annual meeting of the Forum for Information Retrieval Evaluation. ACM International Conference Proceeding Series, Association for Computing Machinery, pp. 7-9, 11th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE 2019, Kolkata, India, 12/12/19. https://doi.org/10.1145/3368567.3368586

On the author profiling and deception detection in Arabic shared task at FIRE. / Rangel, Francisco; Rosso, Paolo; Charfi, Anis et al.
FIRE 2019 - Proceedings of the 11th annual meeting of the Forum for Information Retrieval Evaluation. ed. / Prasenjit Majumder; Mandar Mitra; Surupendu Gangopadhyay; Parth Mehta. Association for Computing Machinery, 2019. p. 7-9 (ACM International Conference Proceeding Series).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

TY - GEN

T1 - On the author profiling and deception detection in Arabic shared task at FIRE

AU - Rangel, Francisco

AU - Rosso, Paolo

AU - Charfi, Anis

AU - Zaghouani, Wajdi

AU - Ghanem, Bilal

AU - Sánchez-Junquera, Javier

PY - 2019/12/12

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N2 - This paper summarises the Author Profiling and Deception Detection in Arabic (APDA) shared task at PAN@FIRE 2019. Two have been the main aims of this year’s task: i) to profile the age, gender and native language of a Twitter user; ii) to determine whether an Arabic text is deceptive or not in two different genres: Twitter and news headlines. For this purpose we have created three corpora in Arabic. Altogether, the approaches of 13 participants are evaluated.

AB - This paper summarises the Author Profiling and Deception Detection in Arabic (APDA) shared task at PAN@FIRE 2019. Two have been the main aims of this year’s task: i) to profile the age, gender and native language of a Twitter user; ii) to determine whether an Arabic text is deceptive or not in two different genres: Twitter and news headlines. For this purpose we have created three corpora in Arabic. Altogether, the approaches of 13 participants are evaluated.

KW - Arabic

KW - Author profiling

KW - Deception detection

KW - FIRE

KW - Twitter

UR - https://www.scopus.com/pages/publications/85077512999

U2 - 10.1145/3368567.3368586

DO - 10.1145/3368567.3368586

M3 - Conference contribution

AN - SCOPUS:85077512999

T3 - ACM International Conference Proceeding Series

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EP - 9

BT - FIRE 2019 - Proceedings of the 11th annual meeting of the Forum for Information Retrieval Evaluation

A2 - Majumder, Prasenjit

A2 - Mitra, Mandar

A2 - Gangopadhyay, Surupendu

A2 - Mehta, Parth

PB - Association for Computing Machinery

T2 - 11th Annual Meeting of the Forum for Information Retrieval Evaluation, FIRE 2019

Y2 - 12 December 2019 through 15 December 2019

ER -

Rangel F, Rosso P, Charfi A, Zaghouani W, Ghanem B, Sánchez-Junquera J. On the author profiling and deception detection in Arabic shared task at FIRE. In Majumder P, Mitra M, Gangopadhyay S, Mehta P, editors, FIRE 2019 - Proceedings of the 11th annual meeting of the Forum for Information Retrieval Evaluation. Association for Computing Machinery. 2019. p. 7-9. (ACM International Conference Proceeding Series). doi: 10.1145/3368567.3368586

On the author profiling and deception detection in Arabic shared task at FIRE

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