India experiences more government-induced internet shutdowns than any other country the world (AccessNow, 2023a), with a tally of 1,978 district-level shutdowns from 2016 to the end of 2022. To better understand these shutdowns, and their effects on political and economic outcomes in India, we need detailed spatio-temporal data on where and when the shutdowns took place. My data set attempts to brige this gap by making internet shutdowns data accessable and easy to use for researchers and the public alike by aligning available data with GADM level 2 naming conventions.
- Imported the different sheets from #KeepitOn Shutdown Tracker Optimization Project (STOP) for 2016-2022 (Access Now, 2023b). The raw collected data can be accessed through https://docs.google.com/spreadsheets/d/1DvPAuHNLp5BXGb0nnZDGNoiIwEeu2ogdXEIDvT4Hyfk/edit#gid=798303217. The methodology for how the data was collected is outlined in the following PDF: https://www.accessnow.org/wp-content/uploads/2023/03/Read-Me_STOP_data_methodology.pdf (updated 2023).
- Gone through all 1978 obesevation (shutdowns) and extracted “state” and “districts” based on “area_name_string.” Manually verified fuzzy-matching. Added GADM level 2 naming conventions to all districts (https://gadm.org/download_country.html). For state-wide shutdowns, districts have been identified by triangulating information based on URLs supplied in #keepiton’s original data set. If additional districts where identified they were added manually to the "districts"-column.
- Merged all files into a full time series from 2016 to 2022, cleaned inconsistencies in each column.
- Calculated duration of each shutdown where data was available.
start_date: start date of shutdown in "%Y/%m/%d" format.
end_date: end date of shutdown in "%Y/%m/%d" format.
duration_days: the duration of the shutdown in days (1 day is 24 hours).
duration_hours: the duration of the shutdown in hours.
country: India.
state: state in India. GADM level 1 naming.
districts: district in India. GADM level 2 naming.
event: what happened where the shutdown took place.
area_name_string: original string denoting the area where it took place by #KeepitOn.
ordered_by: the government authority (Local, State etc.) who issued the shutdown.
gov_justification: the government justification for the shutdown (if any).
affected_network: the network affected by the shutdown.
actual_cause: actual cause of the shutdown as estimated by #KeepitOn.
source_link: source of information (URL).
gov_ack_source: government acknowledgement or official document describing the shutdown (URL).
R code can be run sequentially, starting with script “1_(...)” and ending with script “4_(...)”. This codebook refers to the output data, the .rds file "shutdowns_india_2016_22.rds". For more details, read Koning_Shutdowns_India.pdf
[1] Access Now. (2023a, 20. March). Five years in a row: India is 2022’s biggest internet shutdowns offender. Access Now. https://www.accessnow.org/press-release/keepiton-internet-shutdowns-2022-india/
[2] Access Now. (2023b, 19. May). KeepItOn: Fighting internet shutdowns around the world. Access Now. https://www.accessnow.org/campaign/keepiton/