Analyzing the "Sleeping Giants" Activism Model in Brazil

Bárbara Gomes Ribeiro, Manoel Horta Ribeiro, Virgilio Almeida, Wagner Meira Jr.
2022 14th ACM Web Science Conference 2022  
In 2020, amidst the COVID pandemic and a polarized political climate, the Sleeping Giants online activist movement gained traction in Brazil. Its rationale was simple: to curb the spread of disinformation by harming the advertising revenue of sources that produce this type of content. Like its international counterparts, Sleeping Giants Brasil (SGBR) campaigned against media outlets using Twitter to ask companies to remove ads from the targeted outlets. This work presents a thorough
more » ... characterization of this activism model, analyzing the three campaigns carried out by SGBR between May and September 2020. To do so, we use digital traces from both Twitter and Google Trends, toxicity and sentiment classifiers trained for the Portuguese language, and an annotated corpus of SGBR's tweets. Our key findings were threefold. First, we found that SGBR's requests to companies were largely successful (with 83.85% of all 192 targeted companies responding positively) and that user pressure was correlated to the speed of companies' responses. Second, there were no significant changes in the online attention and the user engagement going towards the targeted media outlets in the six months that followed SGBR's campaign (as measured by Google Trends and Twitter engagement). Third, we observed that user interactions with companies changed only transiently, even if the companies did not respond to SGBR's request. Overall, our results paint a nuanced portrait of internet activism. On the one hand, they suggest that SGBR was successful in getting companies to boycott specific media outlets, which may have harmed their advertisement revenue stream. On the other hand, they also suggest that the activist movement did not impact the online popularity of these media outlets nor the online image of companies that did not respond positively to its requests.
doi:10.1145/3501247.3531563 fatcat:m5lsav3kffglthqkri4aaaoxiy