Architectural styles of curiosity in global Wikipedia mobile app readership

Description of the data and file structure

These directories contain the code, aggregated data, and preprocessing scripts to re-create the figures in "Architectural styles of curiosity in global Wikipedia readership"

Files and variables

File: Archive.zip

Figures: Publically usable illustrations are available here. 

Description: Contains analysis, data, preprocessing, results, and utils folders. 14 directories, 25 files.

|-- analysis
|   |-- KNOT_analysis.R <- analyzes laboratory data
|   |-- analyze_1000-networks.ipynb <- analyzes naturalistic data
|   |-- analyze_1000-networks_comparison-knot-rw_clean.ipynb <- compares datasets and nulls
|   |-- analyze_KNOT_networks.ipynb <- analyzes laboratory data
|   |-- analyze_forward_flow.ipynb <- calculates forward flow
|   |-- forest_plots.R <- correlations wtih sociodemographic variables
|   |-- topic_analysis.R <- analysis of topic and information diversity
|   `-- worldmap.R <- visualization of geographical data sources
|-- data
|   |-- laboratory_data <- variables for laboratory browsing and survey data
|   |-- mobile_app_data <- aggregated data for network structure and topic (rows are individuals)
|   |-- pretrained_embeddings <- fastText word embeddings
|   |-- spatial_navigation <- data from Sea Hero Quest
|   |-- surveys <- data from nationally aggregated sociodemographic surveys
|   `-- wikispeedia <- data from WikiSpeedia game
|-- preprocessing
|   |-- data_knowledge-networks_generate-subsample_clean.ipynb <- processes mobile app data
|   |-- data_knowledge-networks_metrics-combined_clean.ipynb <- calculates network metrics
|   |-- data_knowledge-networks_rw_get-data.ipynb <- calculates null networks
|   `-- data_knowledge-networks_sessions-app_cleaned.ipynb <- processes individual browsing
|-- requirements.txt
|-- results
|   |-- UMAP <- data used to generate network embedding (rows are individuals)
|   `-- figs <- code for generated figure on forward flow 
`-- utils
    |-- plot_knowledge-networks_network-comparison.ipynb <- visualizations of network comparisons
    |-- plot_knowledge-networks_network-metrics_distance.ipynb <- visualizations of distance between datasets
    |-- plot_knowledge-networks_summary-stats.ipynb <- visualizations of summary stats
    |-- utils_embedding.py <- get word and document embeddings
    |-- utils_filtration_metrics.py <- higher-order topology functions (unused)
    |-- utils_gt.py <- graph-tool functions
    |-- utils_network.py <- functions to make networks from series of article IDs
    |-- utils_network_metrics.py <- network metrics
    |-- utils_networkx.py <- networkx functions
    |-- utils_rw.py <- functions to generate random walks and null models
    `-- utils_tokenizer.py <- functions for processing embeddings.

Code/software

See requirements.txt

Access information

Other publicly accessible locations of the data:

* https://gitlab.wikimedia.org/repos/research/curiosity

Additional data was derived from the following sources:

* [Human Development Index]
* [World Happiness Report]
* [WikiSpeedia]
* [FastText]
* [Sea Hero Quest]
* [Knowledge Networks Over Time Study]