Developed by tech-savvy citizens, Rosie is a bot that autonomously checks the public spending of elected representatives of the Brazilian Lower Chamber and uses Twitter to engage peoplein discussing suspicious findings. Rosie is the most visible face of Operação Serenata de Amor (Operation Love Serenade), a data-enabled activism initiative that revolves around the creation, use and dissemination of open data to hold politicians accountable and empower citizens to react against the misuse of public funds. The article draws on an original data set – including interviews, participant online observation notes and secondary qualitative materials – to examine Operação Serenata de Amor, focusing on how material and symbolic elements related to both human and non-human actors shape the organisational patterns of this type of initiative. The findings suggest that there are three organisational patterns, each with further specific challenges, based on the presence of three modes of participation that depend on different types of engagement with digital technologies and data. Findings indicate that data-enabled activism can emerge with typical characteristics and values of tech startups, such as the goal of creating a sustainable budget and providing strategic content by validating it with user feedback, while also retaining some traits of online activism, such as ad hoc and temporal networks of highly autonomous actors concerned with specific contentious issues. In this respect, the eventual demobilisation of Operação Serenata de Amor's initiators due to commercial values and struggles to maintain it active and engaging can be seen as a cautionary tale for data-enabled activism, particularly for initiatives closely associated with civic innovation and social tech startups.

Odilla, F., Mattoni, A. (2023). Unveiling the layers of data activism: the organising of civic innovation to fight corruption in Brazil. BIG DATA & SOCIETY, 02, 1-23 [10.1177/20539517231190078].

Unveiling the layers of data activism: the organising of civic innovation to fight corruption in Brazil

Odilla, Fernanda
Primo
;
Mattoni, Alice
Secondo
2023

Abstract

Developed by tech-savvy citizens, Rosie is a bot that autonomously checks the public spending of elected representatives of the Brazilian Lower Chamber and uses Twitter to engage peoplein discussing suspicious findings. Rosie is the most visible face of Operação Serenata de Amor (Operation Love Serenade), a data-enabled activism initiative that revolves around the creation, use and dissemination of open data to hold politicians accountable and empower citizens to react against the misuse of public funds. The article draws on an original data set – including interviews, participant online observation notes and secondary qualitative materials – to examine Operação Serenata de Amor, focusing on how material and symbolic elements related to both human and non-human actors shape the organisational patterns of this type of initiative. The findings suggest that there are three organisational patterns, each with further specific challenges, based on the presence of three modes of participation that depend on different types of engagement with digital technologies and data. Findings indicate that data-enabled activism can emerge with typical characteristics and values of tech startups, such as the goal of creating a sustainable budget and providing strategic content by validating it with user feedback, while also retaining some traits of online activism, such as ad hoc and temporal networks of highly autonomous actors concerned with specific contentious issues. In this respect, the eventual demobilisation of Operação Serenata de Amor's initiators due to commercial values and struggles to maintain it active and engaging can be seen as a cautionary tale for data-enabled activism, particularly for initiatives closely associated with civic innovation and social tech startups.
2023
Odilla, F., Mattoni, A. (2023). Unveiling the layers of data activism: the organising of civic innovation to fight corruption in Brazil. BIG DATA & SOCIETY, 02, 1-23 [10.1177/20539517231190078].
Odilla, Fernanda; Mattoni, Alice
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/935794
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