Paper by Chitu Okoli: “The ongoing debates in the information systems (IS) discipline on the nature of theory are implicitly rooted in different epistemologies of the social sciences and in a lack of consensus on a definition of theory. Thus, we focus here on the much-neglected topic of what constitutes the bare minimum of what can possibly be considered theory—only by carefully understanding the bare minimum can we really understand the essence of what makes a theory a theory. We definitionally define a theory in the social sciences as an explanation of the relationship between two or more measurable concepts. (“Measurable” refers to qualitative coding and inference of mechanisms, as well as quantitative magnitudes.) The rigorous justification of each element of this definition helps to resolve issues such as providing a consistent basis of determining what qualifies as theory; the value of other knowledge contributions that are not theory; how to identify theories regardless of if they are named; and a call to recognize diverse forms of theorizing across the social science epistemologies of positivism, interpretivism, critical social theory, critical realism, and pragmatism. Although focused on IS, most of these issues are pertinent to any scholarly discipline within the social sciences…(More)”.
Can politicians and citizens deliberate together? Evidence from a local deliberative mini-public
Paper by Kimmo Grönlund, Kaisa Herne, Maija Jäske, and Mikko Värttö: “In a deliberative mini-public, a representative number of citizens receive information and discuss given policy topics in facilitated small groups. Typically, mini-publics are most effective politically and can have the most impact on policy-making when they are connected to democratic decision-making processes. Theorists have put forward possible mechanisms that may enhance this linkage, one of which is involving politicians within mini-publics with citizens. However, although much research to date has focussed on mini-publics with many citizen participants, there is little analysis of mini-publics with politicians as coparticipants. In this study, we ask how involving politicians in mini-publics influences both participating citizens’ opinions and citizens’ and politicians’ perceptions of the quality of the mini-public deliberations. We organised an online mini-public, together with the City of Turku, Finland, on the topic of transport planning. The participants (n = 171) were recruited from a random sample and discussed the topic in facilitated small groups (n = 21). Pre- and postdeliberation surveys were collected. The effect of politicians on mini-publics was studied using an experimental intervention: in half of the groups, local politicians (two per group) participated, whereas in the other half, citizens deliberated among themselves. Although we found that the participating citizens’ opinions changed, no trace of differences between the two treatment groups was reported. We conclude that politicians, at least when they are in a clear minority in the deliberating small groups, can deliberate with citizens without negatively affecting internal inclusion and the quality of deliberation within mini-publics….(More)”.
Mobile phone data reveal the effects of violence on internal displacement in Afghanistan
Paper by Nearly 50 million people globally have been internally displaced due to conflict, persecution and human rights violations. However, the study of internally displaced persons—and the design of policies to assist them—is complicated by the fact that these people are often underrepresented in surveys and official statistics. We develop an approach to measure the impact of violence on internal displacement using anonymized high-frequency mobile phone data. We use this approach to quantify the short- and long-term impacts of violence on internal displacement in Afghanistan, a country that has experienced decades of conflict. Our results highlight how displacement depends on the nature of violence. High-casualty events, and violence involving the Islamic State, cause the most displacement. Provincial capitals act as magnets for people fleeing violence in outlying areas. Our work illustrates the potential for non-traditional data sources to facilitate research and policymaking in conflict settings….(More)”.
Automating the Analysis of Online Deliberation? Comparing computational analyses of polarized discussions on climate change to established content analysis
Paper by Lisa Oswald: “High-quality discussions can help people acquire an adequate understanding of issues and alleviate mechanisms of opinion polarization. However, the extent to which the quality of the online public discourse contributes is contested. Facing the importance and the sheer volume of online discussions, reliable computational approaches to assess the deliberative quality of online discussions at scale would open a new era of deliberation research. But is it possible to automate the assessment of deliberative quality? I compare structural features of discussion threads and simple text-based measures to established manual content analysis by applying all measures to online discussions on ‘Reddit’ that deal with the 2020 wildfires in Australia and California. I further com pare discussions between two ideologically opposite online communities, one featuring discussions in line with the scientific consensus and one featuring climate change skepticism. While no single computational measure can capture the multidimensional concept of deliberative quality, I find that (1) measures of structural complexity capture engagement and participation as preconditions for deliberation, (2) the length of comments is correlated with manual measures of argumentation, and (3) automated toxicity scores are correlated with manual measures of respect. While the presented computational approaches cannot replace indepth content coding, the findings imply that selected automated measures can be useful, scalable additions to the measurement repertoire for specific dimensions of online deliberation. I discuss implications for communication research and platform regulation and suggest interdisciplinary research to synthesize past content coding efforts using machine learning….(More)”.
GDPR and the Lost Generation of Innovative Apps
Paper by Rebecca Janßen, Reinhold Kesler, Michael E. Kummer & Joel Waldfogel: “Using data on 4.1 million apps at the Google Play Store from 2016 to 2019, we document that GDPR induced the exit of about a third of available apps; and in the quarters following implementation, entry of new apps fell by half. We estimate a structural model of demand and entry in the app market. Comparing long-run equilibria with and without GDPR, we find that GDPR reduces consumer surplus and aggregate app usage by about a third. Whatever the privacy benefits of GDPR, they come at substantial costs in foregone innovation…(More)”.
More than just information: what does the public want to know about climate change?
Paper by Michael Murunga et all: “Public engagement on climate change is a vital concern for both science and society. Despite more people engaging with climate change science today, there remains a high-level contestation in the public sphere regarding scientific credibility and identifying information needs, interests, and concerns of the non-technical public. In this paper, we present our response to these challenges by describing the use of a novel “public-powered” approach to engaging the public through submitting questions of interest about climate change to climate researchers before a planned engagement activity. Employing thematic content analysis on the submitted questions, we describe how those people we engaged with are curious about understanding climate change science, including mitigating related risks and threats by adopting specific actions. We assert that by inviting the public to submit their questions of interest to researchers before an engagement activity, this step can inform why and transform how actors engage in reflexive dialogue…(More)”.
(When) Do Open Budgets Transform Lives? Progress and Next Steps in Fiscal Openness Research
Paper by Xiao Hui Tai, Shikhar Mehra & Joshua E. Blumenstock: “This paper documents the rapidly growing empirical literature that can plausibly claim to identify causal effects of transparency or participation in budgeting in a variety of contexts. Recent studies convincingly demonstrate that the power of audits travels well beyond the context of initial field-defining studies, consider participatory budgeting beyond Brazil, where such practices were pioneered, and examine previously neglected outcomes, notably revenues and procurement. Overall, the study of the impacts of fiscal openness has become richer and more nuanced. The most well-documented causal effects are positive: lower corruption and enhanced accountability at the ballot box. Moreover, these impacts have been shown to apply across different settings. This research concludes that the empirical case for open government in this policy area is rapidly growing in strength. This paper sets out challenges related to studying national-level reforms; working directly with governments; evaluating systems as opposed to programs; clarifying the relationship between transparency and participation; and understanding trade-offs for reforms in this area….(More)”.
Can behavioral interventions be too salient? Evidence from traffic safety messages
Article by Jonathan D. Hall and Joshua M. Madsen: “Policy-makers are increasingly turning to behavioral interventions such as nudges and informational campaigns to address a variety of issues. Guidebooks say that these interventions should “seize people’s attention” at a time when they can take the desired action, but little consideration has been given to the costs of seizing one’s attention and to the possibility that these interventions may crowd out other, more important, considerations. We estimated these costs in the context of a widespread, seemingly innocuous behavioral campaign with the stated objective of reducing traffic crashes. This campaign displays the year-to-date number of statewide roadside fatalities (fatality messages) on previously installed highway dynamic message signs (DMSs) and has been implemented in 28 US states.
We estimated the impact of displaying fatality messages using data from Texas. Texas provides an ideal setting because the Texas Department of Transportation (TxDOT) decided to show fatality messages starting in August 2012 for 1 week each month: the week before TxDOT’s monthly board meeting (campaign weeks). This allows us to measure the impact of the intervention, holding fixed the road segment, year, month, day of week, and time of day. We used data on 880 DMSs and all crashes occurring in Texas between 1 January 2010 and 31 December 2017 to investigate the effects of this safety campaign. We estimated how the intervention affects crashes near DMSs as well as statewide. As placebo tests, we estimated whether the chosen weeks inherently differ using data from before TxDOT started displaying fatality messages and data from upstream of DMSs.
Contrary to policy-makers’ expectations, we found that displaying fatality messages increases the number of traffic crashes. Campaign weeks realize a 1.52% increase in crashes within 5 km of DMSs, slightly diminishing to a 1.35% increase over the 10 km after DMSs. We used instrumental variables to recover the effect of displaying a fatality message and document a significant 4.5% increase in the number of crashes over 10 km. The effect of displaying fatality messages is comparable to raising the speed limit by 3 to 5 miles per hour or reducing the number of highway troopers by 6 to 14%. We also found that the total number of statewide on-highway crashes is higher during campaign weeks. The social costs of these fatality messages are large: Back-of-the-envelope calculations suggest that this campaign causes an additional 2600 crashes and 16 fatalities per year in Texas alone, with a social cost of $377 million per year…(More)”.
A Computational Inflection for Scientific Discovery
Paper by Tom Hope, Doug Downey, Oren Etzioni, Daniel S. Weld, and Eric Horvitz: “We stand at the foot of a significant inflection in the trajectory of scientific discovery. As society continues on its fast-paced digital transformation, so does humankind’s collective scientific knowledge and discourse. We now read and write papers in digitized form, and a great deal of the formal and informal processes of science are captured digitally — including papers, preprints and books, code and datasets, conference presentations, and interactions in social networks and communication platforms. The transition has led to the growth of a tremendous amount of information, opening exciting opportunities for computational models and systems that analyze and harness it. In parallel, exponential growth in data processing power has fueled remarkable advances in AI, including self-supervised neural models capable of learning powerful representations from large-scale unstructured text without costly human supervision. The confluence of societal and computational trends suggests that computer science is poised to ignite a revolution in the scientific process itself.
However, the explosion of scientific data, results and publications stands in stark contrast to the constancy of human cognitive capacity. While scientific knowledge is expanding with rapidity, our minds have remained static, with severe limitations on the capacity for finding, assimilating and manipulating information. We propose a research agenda of task-guided knowledge retrieval, in which systems counter humans’ bounded capacity by ingesting corpora of scientific knowledge and retrieving inspirations, explanations, solutions and evidence synthesized to directly augment human performance on salient tasks in scientific endeavors. We present initial progress on methods and prototypes, and lay out important opportunities and challenges ahead with computational approaches that have the potential to revolutionize science…(More)”.
Using mobile money data and call detail records to explore the risks of urban migration in Tanzania
Paper by Rosa Lavelle-Hill: “Understanding what factors predict whether an urban migrant will end up in a deprived neighbourhood or not could help prevent the exploitation of vulnerable individuals. This study leveraged pseudonymized mobile money interactions combined with cell phone data to shed light on urban migration patterns and deprivation in Tanzania. Call detail records were used to identify individuals who migrated to Dar es Salaam, Tanzania’s largest city. A street survey of the city’s subwards was used to determine which individuals moved to more deprived areas. t-tests showed that people who settled in poorer neighbourhoods had less money coming into their mobile money account after they moved, but not before. A machine learning approach was then utilized to predict which migrants will move to poorer areas of the city, making them arguably more vulnerable to poverty, unemployment and exploitation. Features indicating the strength and location of people’s social connections in Dar es Salaam before they moved (‘pull factors’) were found to be most predictive, more so than traditional ‘push factors’ such as proxies for poverty in the migrant’s source region…(More)”.