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Computer Science > Computation and Language

arXiv:1808.07674 (cs)
[Submitted on 23 Aug 2018]

Title:Arap-Tweet: A Large Multi-Dialect Twitter Corpus for Gender, Age and Language Variety Identification

Authors:Wajdi Zaghouani, Anis Charfi
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Abstract:In this paper, we present Arap-Tweet, which is a large-scale and multi-dialectal corpus of Tweets from 11 regions and 16 countries in the Arab world representing the major Arabic dialectal varieties. To build this corpus, we collected data from Twitter and we provided a team of experienced annotators with annotation guidelines that they used to annotate the corpus for age categories, gender, and dialectal variety. During the data collection effort, we based our search on distinctive keywords that are specific to the different Arabic dialects and we also validated the location using Twitter API. In this paper, we report on the corpus data collection and annotation efforts. We also present some issues that we encountered during these phases. Then, we present the results of the evaluation performed to ensure the consistency of the annotation. The provided corpus will enrich the limited set of available language resources for Arabic and will be an invaluable enabler for developing author profiling tools and NLP tools for Arabic.
Comments: Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018)
Subjects: Computation and Language (cs.CL)
Cite as: arXiv:1808.07674 [cs.CL]
  (or arXiv:1808.07674v1 [cs.CL] for this version)
  https://doi.org/10.48550/arXiv.1808.07674

Submission history

From: Wajdi Zaghouani [view email]
[v1] Thu, 23 Aug 2018 09:41:17 UTC (484 KB)
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