Persian Trends corpus: a weekly-updated monitor corpus of news articles

The Persian Trends corpus is a Persian monitor corpus made up of news articles or other sources that are regularly updated from their RSS feeds (newsfeeds). The Persian trends corpus is updated twice a week with new texts and grows by about 5 million words every week. These regular updates enable you to use the Trends diachronic analysis tools and study word usage changes, trending words, and neologisms in Persian.

Corpus size

The Persian Trends corpus has been regularly updated since 2023. As of May 2024, the Irish trends contain more than 180 million words.

Persian Trends corpus in statistics:

Number of words: 180+ million
Number of tokens: 200+ million
Number of sentences: 7+ million
Number of documents: 500+ thousand

Part-of-speech tagset

This corpus is neither part-of-speech tagged nor lemmatized.

How is the Persian Trends corpus updated?

New texts are downloaded every four hours. Every Wednesday, all texts downloaded in 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 Persian Trends corpus

Sketch Engine offers a range of tools to work with this Persian Trends corpus from news articles.

Where to find Trends

The texts in the corpus are timestamped (metadata containing publication date) which enables users to use Trends, the diachronic analysis tool for detecting neologisms and studying word usage changes

Persian Trends

Tools to work with the Persian Trends corpus

A complete set of tools is available to work with this Persian Trends corpus from news to generate:

  • keywords – terminology extraction of one-word units
  • word lists – lists of Irish 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

Trends – diachronic analysis

Adam Kilgarriff, Ondřej Herman, Jan Bušta, Pavel Rychlý and Miloš Jakubíček. DIACRAN: a framework for diachronic analysis. In Corpus Linguistics (CL2015), United Kingdom, July 2015.

Ondřej Herman and Vojtěch Kovář. Methods for Detection of Word Usage over Time. In Seventh Workshop on Recent Advances in Slavonic Natural Language Processing, RASLAN 2013. Brno: Tribun EU, 2013, pp. 79–85. ISBN 978-80-263-0520-0.

TenTen corpora

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).

Genre annotation and topic classification

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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