lewoniewski/wikipedia-sentiment

This dataset provides sentiment annotations for English Wikipedia articles using five different sentiment analysis models, as described in the study “Cross-Topic Sentiment Analysis of Wikipedia Articles: A Comparative Study of AI Models” (see also the supplementary materials for the study).

Dataset Structure

Each record corresponds to a single Wikipedia article and contains sentiment labels produced by multiple models.

Field	Description
page_id	Unique identifier of the Wikipedia article
title	Title of the Wikipedia article
model1	Sentiment label from cVADER (lexicon-based, compound score variant)
model2	Sentiment label from DistilBERT (transformer-based)
model3	Sentiment label from RoBERTa (transformer-based)
model4	Sentiment label from TextBlob (lexicon-based)
model5	Sentiment label from VADER (lexicon-based)

Each model assigns one of the following labels:

• pos – positive
• neu – neutral
• neg – negative

Data Collection and Processing

Source Data

• English Wikipedia dump (March 2025)
• Only main namespace articles (no redirects)

Preprocessing

• Articles were cleaned and extracted using WikiExtractor
• Long articles were split into smaller text segments due to model input limits

Sentiment Inference

• Each segment was analyzed independently by all models
• Transformer models output class probabilities
• Lexicon-based models output polarity scores mapped to classes

Aggregation Method

Similarly to our previous work, we used the advanced aggregation method to obtain the overall sentiment assessment for whole Wikipedia article. Segment-level predictions were aggregated into article-level sentiment using a length-weighted averaging scheme. The final label for each model corresponds to the dominant sentiment class.

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Citation

If you use this dataset, please cite:

@InProceedings{10.1007/978-3-032-18920-2_34,
author="Lewoniewski, W{\l}odzimierz and Str{\'o}{\.{z}}yna, Milena and Czuma{\l}owska, Izabela and Wojewoda, Aleksandra and W{\k{e}}cel, Krzysztof",
title="Cross-Topic Sentiment Analysis of Wikipedia Articles: A Comparative Study of AI Models",
booktitle="Artificial Intelligence for Knowledge Acquisition and Management",
year="2026",
publisher="Springer Nature Switzerland",
address="Cham",
pages="364--370",
isbn="978-3-032-18920-2"
}