Global Database of Events, Language, and Tone

The Global Database of Events, Language, and Tone (GDELT), created by Kalev Leetaru of Yahoo! and Georgetown University, along with Philip Schrodt and others, describes itself as "an initiative to construct a catalog of human societal-scale behavior and beliefs across all countries of the world, connecting every person, organization, location, count, theme, news source, and event across the planet into a single massive network that captures what's happening around the world, what its context is and who's involved, and how the world is feeling about it, every single day."[1][2][3] Early explorations leading up to the creation of GDELT were described by co-creator Philip Schrodt in a conference paper in January 2011.[4] The dataset is available on Google Cloud Platform.[5]

Data

GDELT includes data from 1979 to the present. The data is available as zip files in tab-separated value format using a CSV extension for easy import into Microsoft Excel or similar spreadsheet software.[6] Data from 1979 to 2005 is available in the form of one zip file per year, with the file size gradually increased infrom 14.3 MB in 1979 to 125.9 MB in 2005, reflecting the increase in the number of news media and the frequency and comprehensiveness of event recording.[7] Data files from January 2006 to March 2013 are available at monthly granularity, with the zipped file size rising from 11 MB in January 2006 to 103.2 MB in March 2013. Data files from April 1, 2013 onward are available at a daily granularity. The data file for each date is made available by 6 AM Eastern Standard Time the next day. As of June 2014, the size of the dailly zipped file is about 5-12 MB.[6][7] The data files use Conflict and Mediation Event Observations (CAMEO) coding for recording events.[8]

In a blog post for Foreign Policy, co-creator Kalev Leetaru attempted to use GDELT data to answer the question of whether the Arab Spring sparked protests worldwide, using the quotient of the number of protest-related events to the total number of events recorded as a measure of protest intensity for which the time trend was then studied.[9] Political scientist and data science/forecasting expert Jay Ulfelder critiqued the post on his personal blog, saying that Leetaru's normalization method may not have adequately accounted for the change in the nature and composition of media coverage.[10]

The dataset is also available on Google Cloud Platform and can be accessed using Google BigQuery.[5]

Reception

Academic reception

GDELT has been cited and used in a number of academic studies, such as a study of visual and predictive analytics of Singapore news (along with Wikipedia and the Straits Times Index)[11] and a study of political conflict.[12]

The challenge problem at the 2014 International Social Computing, Behavioral Modeling and Prediction Conference (SBP) asked participants to explore GDELT and apply it to the analysis of social networks, behavior, and prediction.[13]

Reception in blogs and media

GDELT has been covered on the website of the Center for Data Innovation[14] as well as the GIS Lounge.[15] It has also been discussed and critiqued on blogs about political violence and crisis prediction.[10][16][17] The dataset has been cited and critiqued repeatedly in Foreign Policy,[2][18] including in discussions of political events in Syria,[19] the Arab Spring,[9][20] and Nigeria.[21] It has also been cited in New Scientist,[22] on the FiveThirtyEight website[23] and Andrew Sullivan's blog.[24]

The Predictive Heuristics blog and other blogs have compared GDELT with the Integrated Conflict Early Warning System (ICEWS).[25][26] Alex Hanna blogged about her experiment assessing GDELT with handcoded data by comparing it with the Dynamics of Collective Action dataset.[27]

In May 2014, the Google Cloud Platform blog announced that the entire GDELT dataset would be available as a public dataset in Google BigQuery.[5]

See also

References

  1. ↑ "About GDELT: The Global Database of Events, Language, and Tone". Retrieved June 2, 2014.
  2. 1 2 "Mapped: Every Protest on the Planet Since 1979". Foreign Policy. Retrieved June 2, 2014.
  3. ↑ "Global Database of Events, Language, and Tone". datahub.io. Retrieved June 2, 2014.
  4. ↑ Schrodt, Philip (January 20, 2011). "Automated Production of High-Volume, Near-Real-Time Political Event Data" (PDF). Retrieved June 12, 2014.
  5. 1 2 3 "World's largest event dataset now publicly available in BigQuery". Google Cloud Platform. May 29, 2014. Retrieved June 2, 2014.
  6. 1 2 "Raw data files". Global Database of Events, Language, and Tone.
  7. 1 2 "All GDELT Event Files". Retrieved June 12, 2014.
  8. ↑ "Documentation". Global Database of Events, Language, and Tone.
  9. 1 2 Leetaru, Kalev (May 29, 2014). "Did the Arab Spring Really Spark a Wave of Global Protests? The world may look like it's roiling now, but the 1980s were far worse.". Foreign Policy. Retrieved June 2, 2014.
  10. 1 2 Ulfelder, Jay (June 6, 2014). "Another Note on the Limitations of Event Data". Retrieved June 12, 2014.
  11. ↑ Phua, Clifton; Feng, Yuzhang; Ji, Junyao; Soh, Timothy. "Visual and Predictive Analytics on Singapore News: Experiments on GDELT, Wikipedia, and ^STI".
  12. ↑ Yonamine, James E. "A nuanced study of political conflict using the Global Datasets of Events Location and Tone (GDELT) dataset". Retrieved June 2, 2014.
  13. ↑ "SBP 2014 Grand Challenge: explore GDELT, Global Database of Events, Language and Tone". Retrieved June 2, 2014.
  14. ↑ "Creating a Real-Time Global Database of Events, People, and Places in the News". Center for Data Innovation. December 15, 2013. Retrieved June 2, 2014.
  15. ↑ Caitlin Dempsey Morais (September 5, 2013). "Mapping Global Events Since 1979". GIS Lounge. Retrieved June 2, 2014.
  16. ↑ "Raining on the Parade: Some Cautions Regarding the Global Database of Events, Language and Tone Dataset". Political Violence at a Glance. February 20, 2014. Retrieved June 2, 2014.
  17. ↑ Jongman, Berto (January 5, 2014). "Global Database of Events, Language, and Tone (GDELT) — (Old) Big Data to See (New) Crises?". Public Intelligence Blog. Retrieved June 2, 2014.
  18. ↑ Keating, Joshua (April 10, 2013). "What can we learn from the last 200 million things that happened in the world?". Foreign Policy. Retrieved June 2, 2014.
  19. ↑ Keating, Joshua (July 9, 2013). "How Well Does GDELT Follow Events in Syria?". Foreign Policy. Retrieved June 2, 2014.
  20. ↑ Steinert-Threlkeld, Zachary (September 27, 2013). "The Arab Spring and GDELT". Retrieved June 18, 2014.
  21. ↑ Leetaru, Kalev (March 13, 2014). "Mapping Violence and Protests in Nigeria: How Big Data can find the big story.". Foreign Policy. Retrieved June 2, 2014.
  22. ↑ Heaven, Douglas (May 13, 2013). "World's largest events database could predict conflict". New Scientist. Retrieved June 2, 2014.
  23. ↑ Chalabi, Mona (May 6, 2014). "Kidnapping of Girls in Nigeria Is Part of a Worsening Problem (Updated)". FiveThirtyEight. Retrieved June 2, 2014.
  24. ↑ Sullivan, Andrew (May 30, 2014). "Not Your Father’s Global Uprising". Retrieved June 2, 2014.
  25. ↑ mdwardlab (October 17, 2013). "GDELT and ICEWS, a short comparison". Predictive Heuristics. Retrieved June 18, 2014.
  26. ↑ Beieler, John (October 28, 2013). "Noise in GDELT". Retrieved June 21, 2014.
  27. ↑ Hanna, Alex (February 24, 2014). "Assessing GDELT with handcoded protest data". Bad Hessian. Retrieved June 21, 2014.

External links

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