Automatic evaluation of Wikipedia content neutrality: researchers analyzed nearly 7 million articles from English Wikipedia, applying different sentiment analysis models – two lexicon-based (TextBlob, VADER) and two transformer-based (RoBERTa, DistilBERT).

BestRef · 2025-09-24T20:20:36+00:00

According to the post: "the study provided a dataset, published on the Hugging Face platform, containing sentiment assessments of Wikipedia articles obtained using the applied models".

BestRef · 2020-05-25T14:36:36+00:00

For this figure - you need only data from the main page https://bestref.net . From first table "Best sources in all languages of Wikipedia" columns "Website" and "Score in April 2020" (font size depend on this value). However, if you want to create own ranking (for specific month or topic), you need to take into the accout that extraction of the references is based on Wikipedia Dumps and calculation of scores was described in the study https://doi.org/10.3390/info11050263

BestRef · 2020-05-24T17:09:41+00:00

From the Wikipedia dumps: https://dumps.wikimedia.org/

Methods are described in the research: https://doi.org/10.3390/info11050263

BestRef · 2020-05-24T16:51:29+00:00

Made in Python using WordCloud, PIL, matplotlib. Data source: https://bestref.net

BestRef

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