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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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Dagbani Wiki Text

Authors: Naafi, Ibrahim;

Dagbani Wiki Text

Abstract

The Dagbani Sentences Dataset is a collection of sentences in the Dagbani language, a Gur language spoken by the Dagomba people of Northern Ghana. The dataset was obtained by scraping sentences from Wikipedia articles written in Dagbani. Content: The dataset comprises a zip file containing a text file, with each line in the text file representing a sentence from an article on the Dagbani Wikipedia page. The text file is encoded in the UTF-8 encoding format, and covers a wide range of topics from folklore, legends, education, to politics and health, among others. Source: The dataset was compiled by scraping sentences from Wikipedia pages written in Dagbani. The sentences were extracted using web scraping techniques, and the data were collected with proper respect for copyright and usage policies of the Wikimedia Foundation. Use Cases: The Dagbani Sentences Dataset can be valuable for researchers, linguists, and natural language processing (NLP) practitioners interested in the study of the Dagbani language. Particularly, the dataset is best suited for language modelling (GPT, BERT).

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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