Characterizing Partisan Political Narrative Frameworks about COVID-19 on Twitter

The COVID-19 pandemic is a global crisis that has been testing every society and exposing the critical role of local politics in crisis response. In the United States, there has been a strong partisan divide between the Democratic and Republican party's narratives about the pandemic which resulted in polarization of individual behaviors and divergent policy adoption across regions. As shown in this case, as well as in most major social issues, strongly polarized narrative frameworks facilitate such narratives. To understand polarization and other social chasms, it is critical to dissect these diverging narratives. Here, taking the Democratic and Republican political social media posts about the pandemic as a case study, we demonstrate that a combination of computational methods can provide useful insights into the different contexts, framing, and characters and relationships that construct their narrative frameworks which individual posts source from. Leveraging a dataset of tweets from elite politicians in the U.S., we found that the Democrats' narrative tends to be more concerned with the pandemic as well as financial and social support, while the Republicans discuss more about other political entities such as China. We then perform an automatic framing analysis to characterize the ways in which they frame their narratives, where we found that the Democrats emphasize the government's role in responding to the pandemic, and the Republicans emphasize the roles of individuals and support for small businesses. Finally, we present a semantic role analysis that uncovers the important characters and relationships in their narratives as well as how they facilitate a membership categorization process. Our findings concretely expose the gaps in the "elusive consensus" between the two parties. Our methodologies may be applied to computationally study narratives in various domains.Comment: 16 pages, 5 figures. To be published in EPJ Data Scienc

Toxicity in Evolving Twitter Topics - Employing a novel Dynamic Topic volution Model (DyTEM) onTwitter data

Dissertation presented as the partial requirement for obtaining a Master's degree in Data Science and Advanced Analytics, specialization in Data ScienceThis thesis presents an extensive investigation into the evolution of topics and their association with speech toxicity on Twitter, based on a large corpus of tweets, providing crucial insights for monitoring online discourse and potentially informing interventions to combat toxic behavior in digital communities. A Dynamic Topic Evolution Model (DyTEM) is introduced, constructed by combining static Topic Modelling techniques and sentence embeddings through the state-of-the-art sentence transformer, sBERT. The DyTEM, tested and validated on a substantial sample of tweets, is represented as a directed graph, encapsulating the inherent dynamism of Twitter discussions. For validating the consistency of DyTEM and providing guidance for hyperparameter selection, a novel, hashtag-based validation method is proposed. The analysis identifies and scrutinizes five distinct Topic Transition Types: Topic Stagnation, Topic Merge, Topic Split, Topic Disappearance, and Topic Emergence. A speech toxicity classification model is employed to delve into the toxicity dynamics within topic evolution. A standout finding of this study is the positive correlation between topic popularity and its toxicity, implying that trending or viral topics tend to contain more inflammatory speech. This insight, along with the methodologies introduced in this study, contributes significantly to the broader understanding of digital discourse dynamics and could guide future strategies aimed at fostering healthier and more constructive online spaces

Estratégias de persuasão no marketing político : fundamentos morais, fake news e framing

Dissertação (mestrado)—Universidade de Brasília, Instituto de Psicologia, Programa de Pós-Graduação em Psicologia Social, do Trabalho e das Organizações, 2019.Em época de eleições as pessoas facilmente se deparam com jingles políticos, propagandas na TV ou veem políticos abraçando crianças nas ruas. De fato, a persuasão parece desempenhar um papel importante tanto no convencimento de eleitores como no apoio popular para medidas de lei. Por isso, eleitores e pesquisadores se questionam a respeito de quais seriam as estratégias políticos utilizadas por políticos e suas equipes de marketing. Esta dissertação apresenta quatro manuscritos, um teórico e três empíricos, baseados no modelo de probabilidade da elaboração, nos princípios de influência social e na teoria dos fundamentos morais. O Manuscrito 1 descreve e articula a literatura pertinente às táticas de influência social em termos das características do emissor, da mensagem emitida e dos receptores desse conteúdo. O Manuscrito 2 teve como objetivo analisar o uso de estratégias voltadas para mensagem política. Especificamente, analisou o uso de fundamentos morais no plano de governo dos candidatos à presidência nas eleições brasileiras de 2018. De uma forma geral, Jair Bolsonaro usou em maior quantidade fundamentos morais (M = 19,77, DP = 4,24) que Fernando Haddad (M = 9,12, DP = 3,12). Já o Manuscrito 3 investigou o uso de fundamentos morais e princípios de influência social nas notícias falsas mais compartilhadas durante o primeiro turno das eleições 2018 no Brasil. Grupo/lealdade e cuidado/dano foram os fundamentos mais usados, assim como autoridade, empatia e unidade emergiram como os princípios mais frequentes. Por fim, o Manuscrito 4 teve como propósito identificar o efeito de framings morais nas atitudes em relação a questões políticas entre 354 participantes (homens = 64.7%, média de idade = 35,53 anos, DP = 11,87) que responderam a um questionário online. Não foram encontradas diferenças nas condições manipuladas: programa Mais Médicos, F(2, 347) = 0,002, p = 0,998, ηp2 < 0,001; apoio a militares, F(2, 347) = 0,33, p = 0,97, ηp2 < 0,001; e casamento entre pessoas do mesmo sexo, F(2, 347) = 1,5, p = 0,226, ηp2 = 0,009. Discute-se como os quatro estudos contribuem para uma maior compreensão de como se dá a persuasão no contexto político e fornecem informações sistemáticas para cidadãos, agências reguladoras e profissionais de comunicação.Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq).In election times, people are often faced with political jingles, TV advertisements or images of politicians hugging children. In fact, persuasion seems to play an important role both in persuading voters and in the popular support for political projects. Therefore, voters and researchers might question about which strategies politicians use to convince people. To investigate this, the present dissertation is divided into four manuscripts, based on the elaboration likelihood model, the principles of social influence, and the moral foundations theory. Manuscript 1 described and articulated the literature related to social influence tactics in terms of the features of the sender, the message, and the receivers. Manuscript 2 focused on the use of strategies employed in political messages. Specifically, it analyzed to what extent moral foundations were used in the presidential candidates' government plans in the 2018 Brazilian elections. In general, Jair Bolsonaro used more moral foundations (M = 19.77, SE = 4.24) than did Fernando Haddad (M = 9.12, SE = 3.12). Manuscript 3 investigated to what extent moral foundations and principles of social influence were used in the most shared fake news during the first round of the 2018 elections in Brazil. In-group/loyalty and care/harm emerged as the most used foundations, whereas authority, empathy, and unity were the most frequent principles. Finally, Manuscript 4 aimed to identify the effects of moral framings on attitudes toward political issues among 354 participants (male = 64.7%, age mean = 35.53, SD = 11.87) that answered an online questionnaire. No differences were found in the conditions manipulated: More Doctors Program (Programa Mais Médico), F(2, 347) = .002, p = .998, ηp2 = .000; support for the military, F(2, 347) = .3, p = .97, ηp2 = .000; and marriage between people of the same sex, F(2, 347) = 1.5, p = .226, ηp2 = .009. The four studies contribute to a greater understanding of how persuasion and morality work in the political context, and provide systematic information to citizens, regulatory agencies, and communication professionals