Political Polarization in the Brazilian Election Campaign for the Presidency of Brazil in 2018: An Analysis of the Social Network Instagram

Fernandes, Carla Montuori; Oliveira, Luiz Ademir de; Campos, M.; Gomes, Vinícius Borges

doi:10.11114/ijsss.v8i4.4837

Cited by 6 publications

(3 citation statements)

References 8 publications

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“…Then, the social bubble would act as a buffer, shielding the individual from the loss of prestige. The disclosure of this bubble can be demonstrated by the intense polarization of ideas [ 28 , 47 ]. The ideological issue promotes the conformity of ideas or behaviors through the feeling of belonging to a group [ 23 ].…”

Section: Discussionmentioning

confidence: 99%

Cultural Evolution and Digital Media: Diffusion of Fake News About COVID-19 on Twitter

Oliveira

Albuquerque

2021

SN COMPUT. SCI.

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Disinformation (fake news) is a major problem that affects modern populations, especially in an era when information can be spread from one corner of the world to another in just one click. The diffusion of misinformation becomes more problematic when it addresses issues related to health, as it can affect people at both the individual and population levels. Through the ideas proposed by cultural evolution theory, in this study, we seek to understand the dynamics of disseminating messages (cultural traits) with untrue content (maladaptive traits). For our investigation, we used the scenario caused by the Coronavirus Disease 2019 (COVID-19) pandemic as a model. The instability caused by the pandemic provides a good model for the study of adapted and maladaptive traits, as the information can directly affect individual and population fitness. Through data collected on the Twitter platform (259,176 tweets) and using machine learning techniques and web scraping, we built a predictive model to analyze the following questions: (1) Is false information more shared? (2) Is false information more adopted? (3) Do people with social prestige influence the dissemination of maladaptive traits of COVID-19? We observed that fake news features contained in messages with false information were shared and adopted as unblemished messages. We also observed that social prestige was not a determining factor for the diffusion of maladaptive traits. Even with the ability to allow connections between individuals participating in social media, some factors such as attachment to cultural traits and the formation of social bubbles can favor isolation and decrease connectivity between individuals. Consequently, in the scenario of isolation between groups and low connectivity between individuals, there is a reduction in cultural exchange between people, which interferes with the dynamics of the selection of cultural traits. Thus, maladaptive (harmful) traits are favored and maintained in the cultural system. We also argue that the local Brazilian cultural context can be a determining factor for maintaining maladaptive traits. We conclude that in an unstable (pandemic) scenario, the information transmitted on Twitter is not reliable in relation to the increase in fitness, which may occur because of the low cultural exchange promoted by the personalization of the social network and cultural context of the population. Supplementary Information The online version contains supplementary material available at 10.1007/s42979-021-00836-w.

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Section: Discussionmentioning

confidence: 99%

Cultural Evolution and Digital Media: Diffusion of Fake News About COVID-19 on Twitter

Oliveira

Albuquerque

2021

SN COMPUT. SCI.

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“…Motivated by the highly polarized 2018 Brazilian presidential elections (Fernandes et al 2020;Layton et al 2021) and the extensive use of social media platforms by the presidential candidates, we study the politicization of news posts in the context of the 2022 elections. We collected data from three platforms: YouTube, Twitter, and TikTok.…”

Section: Dataset: Youtube Twitter and Tiktokmentioning

confidence: 99%

Topic Shifts as a Proxy for Assessing Politicization in Social Media

Locatelli,

Calais,

Miranda

et al. 2024

ICWSM

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Politicization is a social phenomenon studied by political science characterized by the extent to which ideas and facts are given a political tone. A range of topics, such as climate change, religion and vaccines has been subject to increasing politicization in the media and social media platforms. In this work, we propose a computational method for assessing politicization in online conversations based on topic shifts, i.e., the degree to which people switch topics in online conversations. The intuition is that topic shifts from a non-political topic to politics are a direct measure of politicization – making something political, and that the more people switch conversations to politics, the more they perceive politics as playing a vital role in their daily lives. A fundamental challenge that must be addressed when one studies politicization in social media is that, a priori, any topic may be politicized. Hence, any keyword-based method or even machine learning approaches that rely on topic labels to classify topics are expensive to run and potentially ineffective. Instead, we learn from a seed of political keywords and use Positive-Unlabeled (PU) Learning to detect political comments in reaction to non-political news articles posted on Twitter, YouTube, and TikTok during the 2022 Brazilian presidential elections. Our findings indicate that all platforms show evidence of politicization as discussion around topics adjacent to politics such as economy, crime and drugs tend to shift to politics. Even the least politicized topics had the rate in which their topics shift to politics increased in the lead up to the elections and after other political events in Brazil – an evidence of politicization. The code is available at https://github.com/marceloslo/Topic-Shifts-as-a-Proxy-for-Assessing-Politicization-in-Social-Media.

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“…Much attention has been given to the use of online media to diffuse false information and radical discourses and its association with the polarization of Brazilian society (Ribeiro & Ortellado, 2018). Studies have also analyzed the evolution of polarizing narratives in social networks during the campaigns for the 2018 general elections (Fernandes et al, 2020), the use of bots and automated technologies to interfere with the electoral dispute (Ruediger et al, 2017), and the relationship between computational propaganda, consumption of political information, and rising polarization in Brazil (Machado et al, 2018). As Internet usage grows and online platforms become a crucial space in the country's public sphere, it is clear that the question of whether algorithms affect Brazilian democracy is a problem of utmost relevance (do Nascimento Silva & Silva, 2019).…”

Section: Bubblesmentioning

confidence: 99%

Essays on Technology and Society

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Political Polarization in the Brazilian Election Campaign for the Presidency of Brazil in 2018: An Analysis of the Social Network Instagram

Cited by 6 publications

References 8 publications

Cultural Evolution and Digital Media: Diffusion of Fake News About COVID-19 on Twitter

Cultural Evolution and Digital Media: Diffusion of Fake News About COVID-19 on Twitter

Topic Shifts as a Proxy for Assessing Politicization in Social Media

Essays on Technology and Society

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