Arabic Trends: a daily-updated monitor corpus of news articles
The Arabic Trends corpus is an Arabic monitor corpus made up of news articles or other sources that are regularly updated from their RSS feeds (newsfeeds). The Arabic trends corpus is updated daily with new texts and grows by about 1–2 million words each day. These regular updates enable you to use the diachronic analysis tool and study word usage changes.
The Arabic Trends corpus is tagged by the CAMeL tool using the POS CAMeL tagset.
How are Trends corpora updated?
New texts are downloaded every four hours. Every Wednesday, all texts downloaded the previous week till the end of Sunday are added to the corpus. Duplicate and near-duplicate texts within the same month are removed, but they are kept in different months, e.g. if the same text appears in June twice, only one instance is kept. If the same text appears once in June and once in July, both are kept.
Search the Arabic Trends corpus
Sketch Engine offers a range of tools to work with this Arabic Trends corpus from news articles.
Tools to work with the Arabic Trends corpus
A complete set of tools is available to work with this Arabic Trends corpus from news to generate:
- word sketch – Arabic collocations categorized by grammatical relations
- thesaurus – synonyms and similar words for every word
- keywords – terminology extraction of one-word units
- word lists – lists of Arabic nouns, verbs, adjectives, etc. organized by frequency
- n-grams – frequency list of multi-word units
- concordance – examples in context
- trends – diachronic analysis automatically identifies neologisms and changes in use
- text type analysis – statistics of metadata in the corpus
SUCHOMEL, Vít. Better Web Corpora For Corpus Linguistics And NLP. 2020. Available also from: https://is.muni.cz/th/u4rmz/. Doctoral thesis. Masaryk University, Faculty of Informatics, Brno. Supervised by Pavel RYCHLÝ.
Jakubíček, M., Kilgarriff, A., Kovář, V., Rychlý, P., & Suchomel, V. (2013, July). The TenTen corpus family. In 7th International Corpus Linguistics Conference CL (pp. 125-127).
Suchomel, V., & Pomikálek, J. (2012). Efficient web crawling for large text corpora. In Proceedings of the seventh Web as Corpus Workshop (WAC7) (pp. 39-43).
SUCHOMEL, Vít. Genre Annotation of Web Corpora: Scheme and Issues. In Kohei Arai, Supriya Kapoor, Rahul Bhatia. Proceedings of the Future Technologies Conference (FTC) 2020, Volume 1. Vancouver, Canada: Springer Nature Switzerland AG, 2021. s. 738-754. ISBN 978-3-030-63127-7. doi:10.1007/978-3-030-63128-4_55.
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