Social Data Science Research Articles

Global state of education-related inequality in COVID-19 vaccine coverage, structural barriers, vaccine hesitancy, and vaccine refusal: findings from the Global COVID-19 Trends and Impact Survey

COVID-19 vaccine coverage and experiences of structural and attitudinal barriers to vaccination vary across populations. Education-related inequality in COVID-19 vaccine coverage and barriers within and between countries can provide insight into the hypothesised role of education as a correlate of vaccine access and acceptability. We aimed to characterise patterns of within-country education-related inequality in COVID-19 vaccine indicators across 90 countries. This study used data from the University of Maryland Social Data Science Center Global COVID-19 Trends and Impact Survey. Data from 90 countries (more than 14 million participants aged 18 years and older) were included in our analyses. We assessed education-related inequalities globally, across country-income groupings, and nationally for four indicators (self-reported receipt of COVID-19 vaccine, structural barriers to vaccination, vaccine hesitancy, and vaccine refusal) for the study period June 1-Dec 31, 2021. We calculated an absolute summary measure of inequality to assess the latest situation of inequality and time trends and explored the association between government vaccine availability policies and education-related inequality. Nearly all countries had higher self-reported receipt of a COVID-19 vaccine among the most educated respondents than the least educated respondents. Education-related inequality in structural barriers, vaccine hesitancy, and vaccine refusal varied across countries, and was most pronounced in high-income countries, overall. Low-income and lower-middle-income countries reported widespread experiences of structural barriers and high levels of vaccine hesitancy alongside low levels of education-related inequality. Globally, vaccine hesitancy in unvaccinated people was higher among those with lower education and vaccine refusal was higher among those with higher education, especially in high-income countries. Over the study period, education-related inequalities in self-reported receipt of a COVID-19 vaccine declined, globally and across all country income groupings. Government policies expanding vaccine availability were associated with lower education-related inequality in self-reported receipt of vaccine. This study serves as a baseline for continued inequality monitoring and could help to inform targeted actions for the equitable uptake of vaccines. Gavi, the Vaccine Alliance.

Education-related inequalities in beliefs and behaviors pertaining to COVID-19 non-pharmaceutical interventions

BackgroundThe coronavirus pandemic has exposed existing social inequalities in relation to disease preventive behaviors, risk of exposure, testing and healthcare access, and consequences as a result of illness and containment measures across different population groups. However, due to a lack of data, to date there has been limited evidence of the extent of such within-country inequalities globally.MethodsWe examined education-related inequalities in four COVID-19 prevention and testing indicators within 90 countries, using data from the University of Maryland Social Data Science Center Global COVID-19 Trends and Impact Survey, in partnership with Facebook, over the period 1 June 2021 to 31 December 2021. The overall level of education-related inequalities, as well as how they differ across country income groups and how they have changed over time were analyzed using the Slope Index of Inequality (SII) and the Relative Index of Inequality (RII). We also assessed whether these education-related inequalities were associated with government policies and responses.ResultsEducation-related inequalities in beliefs, mask wearing, social distancing and testing varied across the study countries. Mask wearing and beliefs in the effectiveness of social distancing and mask wearing were overall more common among people with a higher level of education. Even after controlling for other sociodemographic and health-related factors, social distancing practice was higher among the most educated in low/lower middle income countries, but was higher overall among the least educated in high income countries. Overall there were low education-related inequalities in COVID-19 testing, though there was variation across countries.ConclusionsThe study highlights important within-country education-related differences in COVID-19 beliefs, preventive behaviors and testing, as well as differing trends across country income groups. This has implications for considering and targeting specific population groups when designing public health interventions and messaging during the COVID-19 pandemic and future health emergencies.

Privacy-preserving local analysis of digital trace data: A proof-of-concept

SummaryWe present PORT, a software platform for local data extraction and analysis of digital trace data. While digital trace data hold huge potential for social-scientific discovery, their most useful parts have been unattainable for scientists because of privacy concerns and prohibitive access to application programming interfaces. Recently, a workflow was introduced allowing citizens to donate their digital traces to scientists. In this workflow, citizens’ digital traces are processed locally on their machines before providing informed consent to share a subset of the data with researchers. In this paper, we present the newly developed software PORT that implements the local processing part of this workflow, protecting privacy by shielding sensitive data from outside observers, including the researchers themselves. When using PORT, researchers can tailor the local processing procedure suitable to the data download package and research question. Thus, PORT enables a host of potential applications of social data science to hitherto unobtainable data.

Digital bioethics: introducing new methods for the study of bioethical issues

The online space has become a digital public square, where individuals interact and share ideas on the most trivial to the most serious of matters, including discussions of controversial ethical...

Participative epistemology in social data science: combining ethnography with computational and statistical approaches

ABSTRACT In this paper, I introduce the notion of participative epistemology and discuss how it can contribute to make social data science more accountable. I do so by offering the case of a project where ethnographic, computational and sequence analysis methods have been used in combination. By presenting here in greater detail research design and pilot results of a project using professional networking data to understand the careers of IT industry analysts, I suggest a view on the collaboration between data science and social science as coordinated labour. The application of participative epistemology to social data science is articulated in three points: (1) a more tactical view on the partnerships with commercial data where shared value system is not a pre-requisite for coordinated knowledge production; (2) an appreciation for complementarities in perspective between phenomenological sociology, expertise in computer science associated to digitalisation and the narrative positivism linked with the use of statistics and (3) a view on social data science as contributing empirical sociology with new sensitizing concepts, taking ethnography to reflectively address its own presuppositions.

Strategic culture as a (discursive) institution: a proposal for falsifiable theoretical model with computational operationalization

ABSTRACT In spite of theoretical and methodological diversity, the three generations of the strategic culture literature failed to overcome the main challenge of the approach – to account for change in behavior – due to two fallacies: Conceptualizing strategic culture as homogenous on the national level and continuous on the temporal level. However, the recent emergence of fourth generation in the literature offers prospects for overcoming them. The article presents a new, falsifiable theoretical model that pursues this aim. Thus, it begins with discussion of the promise and pitfalls of the fourth generation. Next, the alignment of strategic culture with new institutionalism is explored. This is followed by an introduction of discursive institutionalism and its potential for advancing the fourth-generation theory building. Then, a new falsifiable fourth-generation discursive-institutionalist strategic culture model is presented. The concluding section discusses the operationalization of the model via network analysis using social data science methods.

Strengthening the Resilience of Political Institutions and Processes: A Framework of Analysis

 Democracy itself is under assault from foreign governments and internal threats, such that democratic institutions may not flourish unless social data science puts our existing knowledge and theories about politics, public opinion, and political

Big data and cumulation in the social sciences

ABSTRACT Research using big data has become popular in the social sciences, raising many new questions. This essay focuses on the question of cumulation, and why the kind of cumulation that is characteristic of social data science is more akin to cumulation in the natural sciences. The reasons for this include how research teams are organized and how they compete to exploit certain data sets to improve upon the work of other teams. There are other factors, however, that mitigate against cumulation, including the lack of access to certain datasets and a lack of building on existing findings in the social sciences. Some of these factors pertain to fundamental philosophical issues in social science, including new ideas about the workings of causal explanation. Others relate to the collaboration or absence of collaboration between different disciplines and to the difference between more applied and more academic research. The essay reviews these factors and develops an account of cumulation anchored in a realist philosophy of science and in the practices and tasks of social science research. It concludes with a call for big data research to be more integrated with already ongoing cumulative findings in the social sciences while recognizing that there are several obstacles to such an integration.

Stitching together the heterogeneous party: A complementary social data science experiment

The era of ‘big data’ studies and computational social science has recently given rise to a number of realignments within and beyond the social sciences, where otherwise distinct data formats – dig...

The Data Science of Politics

This article engages with the methods content in Dowding’s book, examining the underlying assumptions regarding political science methodology and data and arguing that these issues deserve a more central role. In particular, the new possibilities for generation and analysis of large-scale data sources from political activity is driving methodological change, requiring a variety of multi-disciplinary expertise, and presenting new ethical challenges. Expansion of the toolkit of political science methodologies to incorporate the growing field of computational social science, or social data science, draws new scientists into the analysis of politics – such as mathematicians, computer scientists and physicists – who bring their own philosophy and practice of theory building, explanation and approach, which may shape the discipline in the future.