Poor attention: The wealth and regional gaps in event attention and coverage on Wikipedia

Repository for "Poor attention: The wealth and regional gaps in event attention and coverage on Wikipedia" as published in PONE .

This repository contains the preprocessed data files as well as code for the main experiments conducted during the creation of the paper.

Dataset and intermediate results

• Event data: Relevant event articles used for computation, as crawled from Wikipedia through Wikidata identifiers
  • data/events/all_events.csv.gz: All Wikipedia event articles collected for this study
  • data/events/disasters_with_deaths.csv.gz: Articles about disasters with additional metadata (e.g., deaths)
• crossval_results: Cross validaiton results and final models for SVC, SVM, Random Forests, and XGBoosted Trees.
• shap: SHAP values as computed from the best model configurations as by the best-performing model identified through cross-validation
• figures: All figures displayed in the paper, along with supplementary results

As crossval_results and shap folders are too large for GitHub, we provide them on Zenodo [1] alongside the other content of this GitHub repository.

Notebooks and Scripts

• util-Directory: Contains helper and util files used by the notebooks in the main directory
• Experiments and Visualizations:
  • model_cross_validation.ipynb: Model cross validation (grid search) to find best configurations for XGBClassifier/XGBRegressors, RandomForestClassifiers/RandomForestRegressors, and SVC/SVR for predicting views and edits. Results of this step are available under the corresponding zenodo link and should be extracted into the crossval_results/-Folder.
  • generate_SHAP.ipynb: SHAP value generation for the best-performing XGBoostClassifiers and XGBRegressors. We compute both SHAP [2] as well as ACV Shapley values [3]. Results of this step are available under the corresponding zenodo link and should be extracted into the shap/-Folder for this repository.
  • plot_metrics.ipynb: Chloropleth (map) plots for article metrics such as article count or median views/edits to articles per region and country
  • plot_shapval.ipynb:
    • Line plots for GDP per capita SHAP values across language editions, with regions as markers
    • Chloropleth (map) plots for the effect of regions across article categories
  • disaster_analysis.ipynb: Experiment in regards to category-specific features, in this case the number of deaths during a disaster (terror attack, earthquake, etc.)

[1] https://doi.org/10.5281/zenodo.7701969
[2] https://github.com/slundberg/shap
[3] https://github.com/salimamoukou/acv00