fmadore/islam-west-africa-collection

Islam West Africa Collection (IWAC)

Dataset Overview

This dataset forms part of the Islam West Africa Collection (IWAC), an open-access digital database curated by Frédérick Madore. The project is hosted at Leibniz-Zentrum Moderner Orient (ZMO).

Expanding on the Islam Burkina Faso Collection (2021), IWAC comprises over 14,000 archival documents, digitized newspaper articles (including both scanned files and web captures via the Wayback Machine), Islamic publications, audiovisual recordings, and photographs documenting Muslim public life in Burkina Faso, Benin, Niger, Nigeria, Togo, and Côte d'Ivoire.

This dataset includes metadata and, where available, full-text content from newspaper articles, Islamic publications, and audiovisual materials, structured into five subsets: articles, audiovisual, documents, publications, and index.

Text Analysis Features

The dataset includes advanced text analysis metrics calculated from the OCR content:

• Lexical Richness (Richesse_Lexicale_OCR): Type-Token Ratio (TTR) measuring vocabulary diversity
• Readability (Lisibilite_OCR): Flesch reading ease score for French texts
• Topic Modeling: BERTopic-based topic discovery and classification using French CamemBERT embeddings
• Sentiment Analysis: Traditional sentiment classification using DistilCamemBERT model optimized for French
• AI-Generated Assessments: Gemini Flash 2.5 and ChatGPT GPT-4.1 mini evaluations of centrality to Islam/Muslims, subjectivity, and polarity

These metrics were computed using custom scripts:

• Lexical Analysis: A lexical richness calculator processes OCR text to generate TTR scores and Flesch readability indices optimized for French language content
• French Lemmatization: Uses spaCy's fr_dep_news_trf model with text normalization (Unicode NFC, ligature expansion, quote standardization) to generate lemmatized text and stop-word-filtered versions
• Semantic Embeddings: Generates vector representations of French summaries using paraphrase-multilingual-mpnet-base-v2 for semantic search and similarity analysis
• Topic Modeling: Uses BERTopic with French CamemBERT embeddings (dangvantuan/sentence-camembert-base) to automatically discover and classify topics from lemmatized text without stopwords. The model combines UMAP dimensionality reduction, HDBSCAN clustering, and CountVectorizer for topic representation, generating topic IDs, probability scores, and human-readable topic labels
• Traditional Sentiment Analysis: Uses the cmarkea/distilcamembert-base-sentiment model to classify text sentiment into POSITIVE, NEGATIVE, or NEUTRAL categories with confidence scores
• AI Sentiment Analysis: Both Gemini Flash 2.5 and ChatGPT GPT-4.1 mini-powered scripts analyze how Islam and Muslims are represented in each article, providing:
  • Centrality assessment (from "Non abordé" to "Très central")
  • Subjectivity scoring (1-5 scale) measuring objectivity in representation
  • Polarity evaluation (from "Très négatif" to "Très positif") of the portrayal
  • Detailed justifications for each assessment

The AI analysis uses structured prompts specifically designed for studying representations of Islam and Muslims in West African francophone media, with built-in caching and error handling for large-scale processing. Both Gemini Flash 2.5 and ChatGPT GPT-4.1 mini models are used to provide comparative AI assessments.

Loading the Dataset

Use the Hugging Face datasets library to access any of the four subsets:

from datasets import load_dataset

# Load newspaper articles
articles_ds = load_dataset("fmadore/iwac-newspaper-articles", name="articles")

# Load audiovisual documents
audiovisual_ds = load_dataset("fmadore/iwac-newspaper-articles", name="audiovisual")

# Load documents (archival materials)
documents_ds = load_dataset("fmadore/iwac-newspaper-articles", name="documents")

# Load Islamic publications
publications_ds = load_dataset("fmadore/iwac-newspaper-articles", name="publications")

# Load index (entities, places, organizations, events, topics)
index_ds = load_dataset("fmadore/iwac-newspaper-articles", name="index")

Dataset Structure

Subset: articles

This subset contains metadata and OCR-processed content from 11,540 newspaper articles.

Fields:

• o:id (string) — Unique item ID from the Omeka repository
• identifier (string) — Internal item identifier (dcterms:identifier)
• url (string) — URL of the item's page on the IWAC website
• PDF (string) — Link to the original PDF file (if available)
• thumbnail (string) — IIIF thumbnail URL of the document
• title (string) — Title of the article (dcterms:title)
• author (string) — Author(s), separated by | (dcterms:creator)
• newspaper (string) — Newspaper title (dcterms:publisher)
• country (string) — Country of publication
• pub_date (string) — Publication date in YYYY-MM-DD format (dcterms:date)
• descriptionAI (string) — Gemini 2.5 Flash generated French summary (bibo:shortDescription)
• embedding_descriptionAI (sequence) — Semantic embeddings of French summaries using paraphrase-multilingual-mpnet-base-v2
• subject (string) — Subject keywords (Events, Organizations, Persons, Topics), separated by | (dcterms:subject)
• spatial (string) — Geographic focus, separated by | (dcterms:spatial)
• language (string) — Language(s), separated by | (dcterms:language)
• nb_pages (float64) — Number of pages (bibo:numPages)
• URL (string) — Original article URL (if applicable) (fabio:hasURL)
• source (string) — Source or provenance (dcterms:source)
• OCR (string) — Full OCR-extracted text (bibo:content)
• nb_mots (float64) — Number of words in the OCR text
• Richesse_Lexicale_OCR (float64) — Lexical richness score of the OCR text
• Lisibilite_OCR (float64) — Readability score of the OCR text
• lemma_text (string) — spaCy fr_dep_news_trf lemmatized text (normalized, alphabetic tokens only)
• lemma_nostop (string) — spaCy lemmatized text with French stopwords removed
• topic_id (float64) — BERTopic-assigned topic identifier (-1 for outliers)
• topic_prob (float64) — Maximum probability score for the assigned topic
• topic_label (string) — Human-readable topic label generated by BERTopic
• sentiment_label (string) — DistilCamemBERT sentiment classification (POSITIVE/NEGATIVE/NEUTRAL)
• sentiment_score (float64) — DistilCamemBERT confidence score for sentiment classification
• chatgpt_centralite_islam_musulmans (string) — ChatGPT GPT-4.1 mini assessment of centrality to Islam/Muslims
• chatgpt_centralite_justification (string) — ChatGPT GPT-4.1 mini justification for centrality assessment
• chatgpt_subjectivite_score (float64) — ChatGPT GPT-4.1 mini subjectivity score (1-5 scale)
• chatgpt_subjectivite_justification (string) — ChatGPT GPT-4.1 mini justification for subjectivity score
• chatgpt_polarite (string) — ChatGPT GPT-4.1 mini polarity assessment
• chatgpt_polarite_justification (string) — ChatGPT GPT-4.1 mini justification for polarity assessment
• gemini_centralite_islam_musulmans (string) — Gemini Flash 2.5 assessment of centrality to Islam/Muslims
• gemini_centralite_justification (string) — Gemini Flash 2.5 justification for centrality assessment
• gemini_subjectivite_score (float64) — Gemini Flash 2.5 subjectivity score
• gemini_subjectivite_justification (string) — Gemini Flash 2.5 justification for subjectivity score
• gemini_polarite (string) — Gemini Flash 2.5 polarity assessment
• gemini_polarite_justification (string) — Gemini Flash 2.5 justification for polarity assessment

Subset: audiovisual

This subset contains metadata from 45 audiovisual documents, including audio and video recordings from Nigerian sources.

Fields:

• o:id (string) — Unique item ID from the Omeka repository
• identifier (string) — Internal item identifier (dcterms:identifier)
• added_date (string) — Date when item was added to Omeka (YYYY-MM-DD format)
• url (string) — URL of the item's page on the IWAC website
• iiif_manifest (string) — IIIF manifest URL for the media item
• PDF (string) — Link to the media file (audio/video, not necessarily PDF)
• thumbnail (string) — IIIF thumbnail URL of the document
• title (string) — Title of the recording (dcterms:title)
• creator (string) — Creator(s) of the recording, separated by | (dcterms:creator)
• publisher (string) — Publisher or broadcasting organization (dcterms:publisher)
• country (string) — Country of origin (Nigeria)
• pub_date (string) — Publication/broadcast date in YYYY-MM-DD format (dcterms:date)
• descriptionAI (string) — AI-generated description (bibo:shortDescription)
• volume (string) — Volume number(s), separated by | (bibo:volume)
• issue (string) — Issue number(s), separated by | (bibo:issue)
• is_part_of (string) — Parent collection or series (dcterms:isPartOf)
• extent (string) — Duration of recording (e.g., "PT208M" for 208 minutes) (dcterms:extent)
• medium (string) — Medium type (e.g., audio, video) (dcterms:medium)
• subject (string) — Subject keywords (Events, Organizations, Persons, Topics), separated by | (dcterms:subject)
• spatial (string) — Geographic focus, separated by | (dcterms:spatial)
• language (string) — Language(s) of the recording, separated by | (dcterms:language)
• source (string) — Source or provenance (dcterms:source)

Subset: documents

This subset contains metadata and OCR-extracted content from 24 documents (archival materials and other non-periodical publications).

Fields:

• o:id (string) — Unique item ID from the Omeka repository
• identifier (string) — Internal item identifier
• url (string) — URL of the item's IWAC page
• PDF (string) — Link to the original PDF file (if available)
• thumbnail (string) — IIIF thumbnail URL
• title (string) — Title of the document
• author (string) — Author(s) of the document, separated by |
• country (string) — Country of publication
• pub_date (string) — Publication date in YYYY-MM-DD format
• descriptionAI (string) — Gemini 2.5 Flash generated French summary
• embedding_descriptionAI (sequence) — Semantic embeddings of French summaries using paraphrase-multilingual-mpnet-base-v2
• subject (string) — Subject keywords (Events, Organizations, Persons, Topics), separated by |
• spatial (string) — Geographic focus, separated by |
• language (string) — Language(s) of the document
• type (string) — Type of document
• nb_pages (float64) — Number of pages
• source (string) — Source or provenance
• rights (string) — Rights information
• OCR (string) — Full OCR-extracted text
• nb_mots (int64) — Number of words in the OCR text

Subset: publications

This subset contains metadata and OCR-extracted content from 1,501 publications (books, pamphlets, and periodicals).

Fields:

• o:id (string) — Unique item ID from the Omeka repository
• identifier (string) — Internal item identifier
• url (string) — URL of the item's IWAC page
• PDF (string) — Link to the original PDF file (if available)
• thumbnail (string) — IIIF thumbnail URL
• title (string) — Title of the publication
• author (string) — Author(s) of the publication, separated by |
• newspaper (string) — Publication/newspaper title
• country (string) — Country of publication
• pub_date (string) — Publication date in YYYY-MM-DD format
• issue (string) — Issue number or identifier
• subject (string) — Subject keywords (Events, Organizations, Persons, Topics), separated by |
• spatial (string) — Geographic focus, separated by |
• language (string) — Language(s) of the publication
• nb_pages (int64) — Number of pages
• URL (string) — Original publication URL (if applicable)
• source (string) — Source or provenance
• OCR (string) — Full OCR-extracted text
• nb_mots (int64) — Number of words in the OCR text

Subset: index

This subset contains metadata for 4,307 authority records and index entries, including persons, organizations, places, events, and topics referenced in the collection. Each entry includes frequency statistics calculated from the articles and publications subsets.

Fields:

• o:id (int64) — Unique item ID from the Omeka repository
• identifier (string) — Internal item identifier (dcterms:identifier)
• url (string) — URL of the item's page on the IWAC website
• thumbnail (string) — IIIF thumbnail URL of the entity (if available)
• Titre (string) — Title or name of the entity (dcterms:title)
• Titre alternatif (string) — Alternative title or name, separated by | (dcterms:alternative)
• Type (string) — Type of entity: "Lieux" (Places), "Personnes" (Persons), "Organisations" (Organizations), "Événements" (Events), "Sujets" (Topics), or "Notices d'autorité" (Authority records)
• Description (string) — Description of the entity (dcterms:description)
• Date création (string) — Creation date (dcterms:created)
• date (string) — Associated date (dcterms:date)
• Relation (string) — Related entities (dcterms:relation), separated by |
• Remplacé par (string) — Replaced by (dcterms:isReplacedBy), separated by |
• Partie de (string) — Part of (dcterms:isPartOf), separated by |
• spatial (string) — Geographic information (dcterms:spatial), separated by |
• A une partie (string) — Has part (dcterms:hasPart), separated by |
• Prénom (string) — First name (for person entities) (foaf:firstName)
• Nom (string) — Last name (for person entities) (foaf:lastName)
• Genre (string) — Gender (for person entities) (foaf:gender)
• Naissance (string) — Birth date (for person entities) (foaf:birthday)
• Coordonnées (string) — Geographic coordinates (for place entities) (curation:coordinates)
• frequency (int64) — Number of times this entity appears in the articles and publications subsets
• first_occurrence (string) — Date of first occurrence in the collection (YYYY-MM-DD format)
• last_occurrence (string) — Date of last occurrence in the collection (YYYY-MM-DD format)
• countries (string) — Countries where this entity appears, separated by |

Citation

If you use this dataset, please cite:

@misc{madore_2025_iwac,
  author       = {Frédérick Madore},
  title        = {Islam West Africa Collection (IWAC)},
  year         = {2025},
  publisher    = {Leibniz-Zentrum Moderner Orient (ZMO)},
  url          = {https://huggingface.co/datasets/fmadore/islam-west-africa-collection},
  version      = {1.0.0}
}