Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset presents a collection of the official local governments' Twitter activity in Buenos Aires Province in Argentina. The collection is entirely in Spanish and was built by crawling each local government's social media accounts and the reactions it received. The collection focuses on the content-based relations established between the local government authorities and the citizens, instead of on the follower/followee relationship. The dataset is useful for studying how government entities manifest themselves in social media and their different ways of transmitting information; and how citizens interact and express their commitment to the government entities. The collection includes the account activities before, during and after the COVID-19 pandemic. Tweets span between 2009 and December 2022. Data was collected using the Twitter API.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset is about artists. It has 6 rows and is filtered where the artworks is Banco de la Ciudad de Buenos Aires – Casa Matriz, Buenos Aires, Argentina. It features 9 columns including birth date, death date, country, and gender.
Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
Comprehensive dataset containing 1 verified Beauty Life locations in Buenos Aires Province, Argentina with complete contact information, ratings, reviews, and location data.
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Attribution 4.0 (CC BY 4.0)https://creativecommons.org/licenses/by/4.0/
License information was derived automatically
This dataset presents a collection of the official local governments' Twitter activity in Buenos Aires Province in Argentina. The collection is entirely in Spanish and was built by crawling each local government's social media accounts and the reactions it received. The collection focuses on the content-based relations established between the local government authorities and the citizens, instead of on the follower/followee relationship. The dataset is useful for studying how government entities manifest themselves in social media and their different ways of transmitting information; and how citizens interact and express their commitment to the government entities. The collection includes the account activities before, during and after the COVID-19 pandemic. Tweets span between 2009 and December 2022. Data was collected using the Twitter API.