English Trends corpus: a weekly-updated monitor corpus of news articles
The English Trends corpus is an English monitor corpus made up of news articles, Wikipedia or other sources that are regularly updated from their RSS feeds (newsfeeds). The English trends corpus is updated weekly with new texts and grows by about 70 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 English.
Corpus size
The English Trends corpus has been regularly updated since 2014, each week the automated process enlarges the corpus by 70 million words. As of April 2024, the English trends contain more than 80 billion words, i.e. 840 times bigger than the British National Corpus.
English Trends corpus in statistics:
| Number of words: | 80+ billion |
| Number of tokens: | 94+ billion |
| Number of sentences: | 4+ billion |
| Number of documents: | 250+ million |
Part-of-speech tagset
The English Trends corpus is tagged by TreeTagger using the Penn Treebank tagset with Sketch Engine modifications.
How is the English Trends corpus 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 English Trends corpus
Sketch Engine offers a range of tools to work with this English 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
Tools to work with the English Trends corpus
A complete set of tools is available to work with this English Trends corpus from news to generate:
- word sketch – English collocations categorized by grammatical relations
- thesaurus – synonyms and similar words for every word
- keywords – terminology extraction of one-word and multi-word units
- word lists – lists of English 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
Bibliography
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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