Arabic corpora for credibility analysis

Ayman Al Zaatari, Rim El Ballouli, Shady Elbassuoni, Wassim El-Hajj, Hazem Hajj, Khaled Shaban, Nizar Habash, Emad Yehya

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

A significant portion of data generated on blogging and microblogging websites is non-credible as shown in many recent studies. To filter out such non-credible information, machine learning can be deployed to build automatic credibility classifiers. However, as in the case with most supervised machine learning approaches, a sufficiently large and accurate training data must be available. In this paper, we focus on building a public Arabic corpus of blogs and microblogs that can be used for credibility classification. We focus on Arabic due to the recent popularity of blogs and microblogs in the Arab World and due to the lack of any such public corpora in Arabic. We discuss our data acquisition approach and annotation process, provide rigid analysis on the annotated data and finally report some results on the effectiveness of our data for credibility classification.

Original languageEnglish (US)
Title of host publicationProceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016
PublisherEuropean Language Resources Association (ELRA)
Pages4396-4401
Number of pages6
ISBN (Electronic)9782951740891
StatePublished - Jan 1 2016
Event10th International Conference on Language Resources and Evaluation, LREC 2016 - Portoroz, Slovenia
Duration: May 23 2016May 28 2016

Other

Other10th International Conference on Language Resources and Evaluation, LREC 2016
CountrySlovenia
CityPortoroz
Period5/23/165/28/16

Fingerprint

credibility
weblog
data acquisition
learning
popularity
Arab
website
Credibility
lack
Blogs
Machine Learning
Web Sites
Arab World
Filter
Blogging
Classifier
Annotation

Keywords

  • Blogs
  • Credibility
  • Crowdsourcing
  • Twitter

ASJC Scopus subject areas

  • Linguistics and Language
  • Library and Information Sciences
  • Language and Linguistics
  • Education

Cite this

Al Zaatari, A., El Ballouli, R., Elbassuoni, S., El-Hajj, W., Hajj, H., Shaban, K., ... Yehya, E. (2016). Arabic corpora for credibility analysis. In Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016 (pp. 4396-4401). European Language Resources Association (ELRA).

Arabic corpora for credibility analysis. / Al Zaatari, Ayman; El Ballouli, Rim; Elbassuoni, Shady; El-Hajj, Wassim; Hajj, Hazem; Shaban, Khaled; Habash, Nizar; Yehya, Emad.

Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016. European Language Resources Association (ELRA), 2016. p. 4396-4401.

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Al Zaatari, A, El Ballouli, R, Elbassuoni, S, El-Hajj, W, Hajj, H, Shaban, K, Habash, N & Yehya, E 2016, Arabic corpora for credibility analysis. in Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016. European Language Resources Association (ELRA), pp. 4396-4401, 10th International Conference on Language Resources and Evaluation, LREC 2016, Portoroz, Slovenia, 5/23/16.
Al Zaatari A, El Ballouli R, Elbassuoni S, El-Hajj W, Hajj H, Shaban K et al. Arabic corpora for credibility analysis. In Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016. European Language Resources Association (ELRA). 2016. p. 4396-4401
Al Zaatari, Ayman ; El Ballouli, Rim ; Elbassuoni, Shady ; El-Hajj, Wassim ; Hajj, Hazem ; Shaban, Khaled ; Habash, Nizar ; Yehya, Emad. / Arabic corpora for credibility analysis. Proceedings of the 10th International Conference on Language Resources and Evaluation, LREC 2016. European Language Resources Association (ELRA), 2016. pp. 4396-4401
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