Constructing a Bilingual Corpus of Parallel Tweets

Hamdy Mubarak, Sabit Hassan, Ahmed Abdelali


Abstract
In a bid to reach a larger and more diverse audience, Twitter users often post parallel tweets—tweets that contain the same content but are written in different languages. Parallel tweets can be an important resource for developing machine translation (MT) systems among other natural language processing (NLP) tasks. In this paper, we introduce a generic method for collecting parallel tweets. Using this method, we collect a bilingual corpus of English-Arabic parallel tweets and a list of Twitter accounts who post English-Arabictweets regularly. Since our method is generic, it can also be used for collecting parallel tweets that cover less-resourced languages such as Serbian and Urdu. Additionally, we annotate a subset of Twitter accounts with their countries of origin and topic of interest, which provides insights about the population who post parallel tweets. This latter information can also be useful for author profiling tasks.
Anthology ID:
2020.bucc-1.3
Volume:
Proceedings of the 13th Workshop on Building and Using Comparable Corpora
Month:
May
Year:
2020
Address:
Marseille, France
Venues:
BUCC | LREC | WS
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
14–21
Language:
English
URL:
https://www.aclweb.org/anthology/2020.bucc-1.3
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.bucc-1.3.pdf