DOI: 10.5281/zenodo.18433471
title: Selective divergence between Grokipedia and Wikipedia articles

description: main_dataset.csv

This dataset consists of paired articles on identical topics collected from Grokipedia (G) and Wikipedia (W). Each row corresponds to a single topic and contains metadata, structural features, linguistic statistics, similarity measures, and bias/factuality scores for both sources. 

Identification and Existence Flags





title: Canonical topic title.




slug: URL-friendly identifier for the topic.




exists_grokipedia: Binary indicator of whether the topic exists in Grokpedia.




exists_wikipedia: Binary indicator of whether the topic exists in Wikipedia.



Structural and Content Features

All variables prefixed with a_ refer to Grokipedia, and b_ refer to Wikipedia.

Document Structure





paragraph_count: Number of paragraphs.




heading_count_h1–h4: Number of headings at each HTML level.




section_count_h2_h4: Number of sections defined by H2–H4 headings.




link_count: Number of internal and external hyperlinks.




image_count: Number of embedded images.




reference_count: Number of references/citations.



Normalized Density Measures





refs_per_1k_words: References per 1,000 words.




links_per_1k_words: Links per 1,000 words.




headings_per_1k_words: Headings per 1,000 words.



Word Counts





clean_word_count: Number of cleaned (tokenized, stopword-filtered) words.




clean_words_alpha: Alphabetic cleaned words only.




raw_visible_words_alpha: Alphabetic visible words before cleaning.



Lexical and Semantic Similarity

Lexical Similarity





lexical_tfidf_cosine: Cosine similarity between TF-IDF vectors.




lexical_jaccard_unigram: Jaccard similarity over unigram sets.




ngram_overlap_1/2/3: Overlap of unigrams, bigrams, and trigrams.



Semantic Similarity





semantic_embed_cosine: Cosine similarity between sentence embeddings.




bertscore_f1: BERTScore F1 semantic similarity.




stylistic_similarity: Composite stylistic similarity metric.



Linguistic and Readability Features

Computed separately for Grokpedia and Wikipedia.

Syntactic and Lexical Properties





avg_sentence_len: Mean sentence length (words).




lexical_diversity: Type-token ratio.




lexical_density: Proportion of content words.



Readability





flesch_kincaid: Flesch–Kincaid grade level.




gunning_fog: Gunning Fog index.




reading_time_min: Estimated reading time in minutes.



POS Distributions





pos_noun, pos_verb, pos_adj, pos_adv: Proportions of part-of-speech categories.



Raw Text Statistics





char_count: Character count.




word_count: Word count.




sentence_count: Sentence count.



Topic and Clustering Metadata





topic_gpt: Topic label generated by GPT-based topic modeling.




clst_k_means: Cluster ID from k-means clustering.




topic_k_means: Human-interpretable topic label from k-means.



Bias, Leaning, and Factuality Measures

Political Leaning

The party leaning metric from this dataset was used to extract the following metrics. 





leaning_Grokipedia: Estimated political leaning score for Grokipedia.




leaning_Wikipedia: Estimated political leaning score for Wikipedia.




leaning_diff_G_minus_W: Difference in leaning (Grokipedia − Wikipedia).



Bias Scores

The bias score from this dataset was used to extract the following metrics. 





bias_Grokipedia: Overall bias score for Grokipedia.




bias_Wikipedia: Overall bias score for Wikipedia.




bias_diff_G_minus_W: Bias difference between sources.



Factuality

The factuality score from this dataset was used to extract the following metrics. 





factual_Grokipedia: Factuality score for Grokpedia.




factual_Wikipedia: Factuality score for Wikipedia.




factual_diff_G_minus_W: Difference in factuality.



Combined Similarity Score





combined_score: Composite score aggregating multiple similarity metrics.



 

ref_domains_per_article_all.csv

 Each row represents a single referenced domain within a specific article.

Identification and Metadata





title: Title of the article in which the reference appears.




platform: Platform hosting the article (Grokpedia, Wikipedia).




rank: Rank of the domain within the article, ordered by frequency of appearance.




domain: Referenced domain name (e.g., nytimes.com, foxnews.com).



Reference Frequency Measures





count_in_article: Number of times the domain is cited within the article.




n_refs_found_article: Total number of references found in the article.



 

Source Quality and Ideology

These variables are extracted from this dataset.





bias: political bias score of the domain.




factual_reporting: Factual reliability score of the domain.