Corpus of African Digital News from 600 Websites Formatted for Text Mining / Computational Text Analysis
<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are a research archivist expert in dataset metadata. Answer the question truthfully.  <|eot_id|><|start_header_id|>user<|end_header_id|> Here is the Description of a dataset. Description:'This dataset includes a corpus 200,000+ news articles published by 600 African news organizations between December 4, 2020 and January 3, 2021. The texts have been pre-processed (punctuation and English stopwords have been removed, features have been lowercased, lemmatized and POS-tagged) and stored in commonly used formats for text mining/computational text analysis. Users are advised to read the documentation for an explanation of the data collection process.This dataset includes the following items:  31 tables (one per day) of lowercased and lemmatized tokens with the following additional variables: POS tags, document id, sentence id, token id and publication date (stored as a tibble).  A single document-feature matrix (DFM) with raw counts of feature frequencies in each news article (stored as a quan' . Please return only a json list of at most 3 Keywords corresponding to the Description:.<|eot_id|><|start_header_id|>assistant<|end_header_id|> {"Answer" : ["Africa","computational","digital news","news","text mining"]} <|eot_id|>
 Here is the Description of a dataset. Description:'This dataset includes a corpus 200,000+ news articles published by 600 African news organizations between December 4, 2020 and January 3, 2021. The texts have been pre-processed (punctuation and English stopwords have been removed, features have been lowercased, lemmatized and POS-tagged) and stored in commonly used formats for text mining/computational text analysis. Users are advised to read the documentation for an explanation of the data collection process.This dataset includes the following items:  31 tables (one per day) of lowercased and lemmatized tokens with the following additional variables: POS tags, document id, sentence id, token id and publication date (stored as a tibble).  A single document-feature matrix (DFM) with raw counts of feature frequencies in each news article (stored as a quan' . Please return only a json list of at most 3 Keywords corresponding to the Description:.
This dataset includes a corpus 200,000+ news articles published by 600 African news organizations between December 4, 2020 and January 3, 2021. The texts have been pre-processed (punctuation and English stopwords have been removed, features have been lowercased, lemmatized and POS-tagged) and stored in commonly used formats for text mining/computational text analysis. Users are advised to read the documentation for an explanation of the data collection process.This dataset includes the following items:  31 tables (one per day) of lowercased and lemmatized tokens with the following additional variables: POS tags, document id, sentence id, token id and publication date (stored as a tibble).  A single document-feature matrix (DFM) with raw counts of feature frequencies in each news article (stored as a quan
Africa; computational; digital news; news; text mining