Moral and Affective Differences in U.S. Immigration Policy Debate on Twitter

Discovery and characterisation of socially polarised communities on social media

Social polarisation processes have become a central phenomenon for the explanation of population behavioural dynamics in today's societies. Although recent works offer solutions for the detection of polarised political communities in social media, there is still a lack of works that allow an adequate characterization of the specific topics on which these divides between social groups are articulated. Our study aims to discover and characterise antagonistic communities on Twitter based on a method that combines the identification of authorities and textual classifiers around three public debates that have recently produced major controversies: (1) vaccination; (2) climate change; and (3) abortion. The proposed method allows the capture of polarised communities with little effort, requiring only the selection of some terms that characterise the topic and some initial authorities. Our findings show that the processes of social polarisation can vary considerably depending on the subject on which the debates are articulated. Specifically, polarisation manifests more prominently in the realms of vaccination and abortion, whereas this divide is less apparent in the context of climate change.

The Moral Foundations of Vaccine Passports

The debate around vaccine passports has been polarising and controversial. Although the measure allows businesses to resume in-person operations and enables transitioning out of lockdown due to the COVID-19 pandemic, some have expressed concerns about liberty violations and discrimination. Understanding the splintered viewpoints can aid businesses in communicating such measures to employees and consumers. We conceptualise the business implementation of vaccine passports as a moral decision rooted in individual values that influence reasoning and emotional reaction. We surveyed support for vaccine passports on a nationally representative sample in the United Kingdom in 2021: April (n = 349), May (n = 328), and July (n = 311). Drawing on the Moral Foundations Theory-binding (loyalty, authority, and sanctity), individualising (fairness and harm), and liberty values-we find that individualising values are a positive predictor and liberty values a negative predictor of support for passports, suggesting adoption hinges on addressing liberty concerns. Longitudinal analysis examining the trajectory of change in support over time finds that individualising foundations positively predict changes in utilitarian and deontological reasoning over time. In contrast, a fall in anger over time predicts increased support towards vaccine passports. Our study can inform business and policy communication strategies of existing vaccine passports, general vaccine mandates, and similar measures in future pandemics.

A scoping review on the use of natural language processing in research on political polarization: trends and research prospects

As part of the "text-as-data" movement, Natural Language Processing (NLP) provides a computational way to examine political polarization. We conducted a methodological scoping review of studies published since 2010 (n = 154) to clarify how NLP research has conceptualized and measured political polarization, and to characterize the degree of integration of the two different research paradigms that meet in this research area. We identified biases toward US context (59%), Twitter data (43%) and machine learning approach (33%). Research covers different layers of the political public sphere (politicians, experts, media, or the lay public), however, very few studies involved more than one layer. Results indicate that only a few studies made use of domain knowledge and a high proportion of the studies were not interdisciplinary. Those studies that made efforts to interpret the results demonstrated that the characteristics of political texts depend not only on the political position of their authors, but also on other often-overlooked factors. Ignoring these factors may lead to overly optimistic performance measures. Also, spurious results may be obtained when causal relations are inferred from textual data. Our paper provides arguments for the integration of explanatory and predictive modeling paradigms, and for a more interdisciplinary approach to polarization research.

Supplementary Information

The online version contains supplementary material available at 10.1007/s42001-022-00196-2.

Designing Digital Participatory Budgeting Platforms: Urban Biking Activism in Madrid

Civic technologies have the potential to support participation and influence decision-making in governmental processes. Digital participatory budgeting platforms are examples of civic technologies designed to support citizens in making proposals and allocating budgets. Investigating the empirical case of urban biking activists in Madrid, we explore how the design of the digital platform Decide Madrid impacted the collaborative practices involved in digital participatory budgeting. We found that the design of the platform made the interaction competitive, where individuals sought to gain votes for their single proposals, rather than consider the relations across proposals and the larger context of the city decisions, even if the institutional process rewarded collective support. In this way, the platforms’ design led to forms of individualistic, competitive, and static participation, therefore limiting the possibilities for empowering citizens in scoping and self-regulating participatory budgeting collaboratively. We argue that for digital participatory budgeting platforms to support cooperative engagements they must be revisable and reviewable while supporting accountability among participants and visibility of proposals and activities.

COVID-19 and prejudice against migrants: the mediating roles of need for cognitive closure and binding moral foundations. A comparative study

What mitigates prejudice against migrants in situations of uncertainty? Addressing this question, we explored how individuals with greater COVID-19 concern perceive migrants as a greater threat and show prejudice against them, indirectly through the mechanism of need for cognitive closure and binding moral foundations.This study was conducted in two European countries: Malta and Italy. Six hundred and seventy-six individuals participated in this quantitative study (Malta: N = 204; Italy N = 472). Results from this study showed that the need for cognitive closure and binding moral foundations mediate the relationship between COVID-19 concern and prejudice against migrants in both countries. When testing the three binding moral foundations (loyalty, authority, and purity), the authority foundation seems to be the most consistent predictor.The implications of the findings contribute to theories about how situational uncertainty caused by COVID-19, together with the need for epistemic certainty and binding morality, contribute to increased prejudiced attitudes against migrants.

Moral Expressions in 280 Characters or Less: An Analysis of Politician Tweets Following the 2016 Brexit Referendum Vote

Ideas about morality are deeply entrenched into political opinions. This article examines the online communication of British parliamentarians from May 2017-December 2019, following the 2016 referendum that resulted in Britain's exit (Brexit) from the European Union. It aims to uncover how British parliamentarians use moral foundations to discuss the Brexit withdrawal agreement on Twitter, using Moral Foundations Theory as a classification basis for their tweets. It is found that the majority of Brexit related tweets contain elements of moral reasoning, especially relating to the foundations of Authority and Loyalty. There are common underlying foundations between parties, but parties express opposing viewpoints within a single foundation. The study provides useful insights into Twitter's use as an arena for moral argumentation, as well as uncovers the politician's uses of moral arguments during Brexit agreement negotiations on Twitter. It contributes to the limited body of work focusing on the moral arguments made by politicians through Twitter.

Walls block waves: Using an inundation metaphor of immigration predicts support for a border wall

From early 20th century headlines to presidential tweets, immigration is described frequently in terms of waves, floods, and tides. Although usage of this inundation metaphor has been widely documented, its potential influence on immigration attitudes has not been assessed empirically. Building from conceptual metaphor theory’s claim that abstract ideas can be grounded in simpler, concrete concepts, we hypothesized that using the inundation metaphor to understand immigration contributes to support for a U.S.—Mexico border wall as a figurative means to block immigrants. Accordingly, social media posts supporting a border wall contained more inundation-metaphoric expressions than messages opposing a wall and messages opposing immigration without reference to a wall (Study 1; N = 4,067). Converging experimental tests show, when controlling for political attitudes, exposure to the inundation metaphor increases support for a border wall (Studies 2a and 2b; N = 737). These findings add to the growing body of evidence that political cognition and policy attitudes are partly motivated by metaphoric comparisons to concrete ideas that are irrelevant in a literal sense.

Moral concerns are differentially observable in language

Language is a psychologically rich medium for human expression and communication. While language usage has been shown to be a window into various aspects of people's social worlds, including their personality traits and everyday environment, its correspondence to people's moral concerns has yet to be considered. Here, we examine the relationship between language usage and the moral concerns of Care, Fairness, Loyalty, Authority, and Purity as conceptualized by Moral Foundations Theory. We collected Facebook status updates (N = 107,798) from English-speaking participants (n = 2691) along with their responses on the Moral Foundations Questionnaire. Overall, results suggested that self-reported moral concerns may be traced in language usage, though the magnitude of this effect varied considerably among moral concerns. Across a diverse selection of Natural Language Processing methods, Fairness concerns were consistently least correlated with language usage whereas Purity concerns were found to be the most traceable. In exploratory follow-up analyses, each moral concern was found to be differentially related to distinct patterns of relational, emotional, and social language. Our results are the first to relate individual differences in moral concerns to language usage, and to uncover the signatures of moral concerns in language.