Context The GDELT Project is the largest, most comprehensive, and highest resolution open database of human society ever created. Just the 2015 data alone records nearly three quarters of a trillion emotional snapshots and more than 1.5 billion location references, while its total archives span more than 215 years, making it one of the largest open-access spatio-temporal datasets in existance and pushing the boundaries of "big data" study of global human society. Its Global Knowledge Graph connects the world's people, organizations, locations, themes, counts, images and emotions into a single holistic network over the entire planet. How can you query, explore, model, visualize, interact, and even forecast this vast archive of human society? Content GDELT 2.0 has a wealth of features in the event database which includes events reported in articles published in 65 live translated languages, measurements of 2,300 emotions and themes, high resolution views of the non-Western world, relevant imagery, videos, and social media embeds, quotes, names, amounts, and more. You may find these code books helpful:
[GDELT Global Knowledge Graph Codebook V2.1] [1] (PDF)
[GDELT Event Codebook V2.0][2] (PDF)
## Querying BigQuery tables You can use the BigQuery Python client library to query tables in this dataset in Kernels. Note that methods available in Kernels are limited to querying data. Tables are at `bigquery-public-data.github_repos.[TABLENAME]`. **[Fork this kernel to get started][98]** to learn how to safely manage analyzing large BigQuery datasets. Acknowledgements You may redistribute, rehost, republish, and mirror any of the GDELT datasets in any form. However, any use or redistribution of the data must include a citation to the GDELT Project and a link to the website (https://www.gdeltproject.org/). [1]: http://data.gdeltproject.org/documentation/GDELT-Global_Knowledge_Graph_Codebook-V2.1.pdf [2]: http://data.gdeltproject.org/documentation/GDELT-Event_Codebook-V2.0.pdf