Showing papers by "Duncan J. Watts published in 2020"
TL;DR: The results suggest that the origins of public misinformedness and polarization are more likely to lie in the content of ordinary news or the avoidance of news altogether as they are in overt fakery.
Abstract: “Fake news,” broadly defined as false or misleading information masquerading as legitimate news, is frequently asserted to be pervasive online with serious consequences for democracy. Using a unique multimode dataset that comprises a nationally representative sample of mobile, desktop, and television consumption, we refute this conventional wisdom on three levels. First, news consumption of any sort is heavily outweighed by other forms of media consumption, comprising at most 14.2% of Americans’ daily media diets. Second, to the extent that Americans do consume news, it is overwhelmingly from television, which accounts for roughly five times as much as news consumption as online. Third, fake news comprises only 0.15% of Americans’ daily media diet. Our results suggest that the origins of public misinformedness and polarization are more likely to lie in the content of ordinary news or the avoidance of news altogether as they are in overt fakery.
217 citations
Northeastern University1, Harvard University2, Massachusetts Institute of Technology3, University of Pennsylvania4, Stanford University5, Northwestern University6, University of North Carolina at Chapel Hill7, University of Oxford8, The Turing Institute9, Social Science Research Council10, Institute for Advanced Study11, Princeton University12, Leibniz Association13, RWTH Aachen University14, University of Koblenz and Landau15
TL;DR: Opportunities to address data sharing, research ethics, and incentives must improve, especially in improving the alignment between the organization of the 20th-century university and the intellectual requirements of the field are suggested.
Abstract: Data sharing, research ethics, and incentives must improve The field of computational social science (CSS) has exploded in prominence over the past decade, with thousands of papers published using observational data, experimental designs, and large-scale simulations that were once unfeasible or unavailable to researchers. These studies have greatly improved our understanding of important phenomena, ranging from social inequality to the spread of infectious diseases. The institutions supporting CSS in the academy have also grown substantially, as evidenced by the proliferation of conferences, workshops, and summer schools across the globe, across disciplines, and across sources of data. But the field has also fallen short in important ways. Many institutional structures around the field—including research ethics, pedagogy, and data infrastructure—are still nascent. We suggest opportunities to address these issues, especially in improving the alignment between the organization of the 20th-century university and the intellectual requirements of the field.
182 citations
Princeton University1, University of California, Los Angeles2, Massachusetts Institute of Technology3, University of Edinburgh4, Montana State University5, University of California, Santa Cruz6, Virginia Tech7, Cornell University8, University of Washington9, University of Oxford10, RTI International11, University of Lincoln12, University of Colorado Boulder13, Tilburg University14, Harvard University15, Indiana University16, New York University Abu Dhabi17, Brigham Young University18, Stanford University19, University of Zurich20, University of Southern California21, Columbia University22, New York University23, Ohio State University24, University of Michigan25, Kyoto University26, Khalifa University27, California State University28, George Washington University29, MDRC30, Northeastern University31, Syracuse University32, The Turing Institute33, University of Cambridge34, University of California, Berkeley35, University of Pennsylvania36
TL;DR: Practical limits to the predictability of life outcomes in some settings are suggested and the value of mass collaborations in the social sciences is illustrated.
Abstract: How predictable are life trajectories? We investigated this question with a scientific mass collaboration using the common task method; 160 teams built predictive models for six life outcomes using data from the Fragile Families and Child Wellbeing Study, a high-quality birth cohort study. Despite using a rich dataset and applying machine-learning methods optimized for prediction, the best predictions were not very accurate and were only slightly better than those from a simple benchmark model. Within each outcome, prediction error was strongly associated with the family being predicted and weakly associated with the technique used to generate the prediction. Overall, these results suggest practical limits to the predictability of life outcomes in some settings and illustrate the value of mass collaborations in the social sciences.
105 citations
Posted Content•
TL;DR: It is found that political news content accounts for a relatively small fraction (11%) of consumption on YouTube, and is dominated by mainstream and largely centrist sources, however, there is evidence for a small but growing "echo chamber" of far-right content consumption.
Abstract: Although it is understudied relative to other social media platforms, YouTube is arguably the largest and most engaging online media consumption platform in the world. Recently, YouTube's outsize influence has sparked concerns that its recommendation algorithm systematically directs users to radical right-wing content. Here we investigate these concerns with large scale longitudinal data of individuals' browsing behavior spanning January 2016 through December 2019. Consistent with previous work, we find that political news content accounts for a relatively small fraction (11%) of consumption on YouTube, and is dominated by mainstream and largely centrist sources. However, we also find evidence for a small but growing "echo chamber" of far-right content consumption. Users in this community show higher engagement and greater "stickiness" than users who consume any other category of content. Moreover, YouTube accounts for an increasing fraction of these users' overall online news consumption. Finally, while the size, intensity, and growth of this echo chamber present real concerns, we find no evidence that they are caused by YouTube recommendations. Rather, consumption of radical content on YouTube appears to reflect broader patterns of news consumption across the web. Our results emphasize the importance of measuring consumption directly rather than inferring it from recommendations.
18 citations
TL;DR: Empirica is a modular virtual lab that offers a solution to the usability–functionality trade-off by employing a “flexible defaults” design strategy, which enables us to maintain complete “build anything” flexibility while offering a development platform that is accessible to novice programmers.
Abstract: Virtual labs allow researchers to design high-throughput and macro-level experiments that are not feasible in traditional in-person physical lab settings Despite the increasing popularity of online research, researchers still face many technical and logistical barriers when designing and deploying virtual lab experiments While several platforms exist to facilitate the development of virtual lab experiments, they typically present researchers with a stark trade-off between usability and functionality We introduce Empirica: a modular virtual lab that offers a solution to the usability-functionality trade-off by employing a "flexible defaults" design strategy This strategy enables us to maintain complete "build anything" flexibility while offering a development platform that is accessible to novice programmers Empirica's architecture is designed to allow for parameterizable experimental designs, reusable protocols, and rapid development These features will increase the accessibility of virtual lab experiments, remove barriers to innovation in experiment design, and enable rapid progress in the understanding of distributed human computation
13 citations
TL;DR: Using multiple measures of preference and test criteria in five preregistered within-subjects studies, it is found that people often disapprove of experiments involving randomization despite approving of the policies or treatments to be tested.
Abstract: We resolve a controversy over two competing hypotheses about why people object to randomized experiments: 1) People unsurprisingly object to experiments only when they object to a policy or treatment the experiment contains, or 2) people can paradoxically object to experiments even when they approve of implementing either condition for everyone. Using multiple measures of preference and test criteria in five preregistered within-subjects studies with 1,955 participants, we find that people often disapprove of experiments involving randomization despite approving of the policies or treatments to be tested.
6 citations
29 Jan 2020
TL;DR: A novel two-phase experiment in which individuals were evaluated on a series of tasks of varying complexity and randomly assigned to solve similar tasks either in groups of different compositions or as individuals finds that average skill level dominates all other factors combined.
Abstract: As organizations gravitate to group-based structures, the problem of improving performance through judicious selection of group members has preoccupied scientists and managers alike. However, it remains poorly understood under what conditions groups outperform comparable individuals, which individual attributes best predict group performance, or how task complexity mediates these relationships. Here we describe a novel two-phase experiment in which individuals were evaluated on a series of tasks of varying complexity; then randomly assigned to solve similar tasks either in groups of different compositions or as individuals. We describe two main sets of findings. First, while groups are more efficient than individuals and comparable “nominal group” when the task is complex, this relationship is reversed when the task is simple. Second, we find that average skill level dominates all other factors combined, including social perceptiveness, skill diversity, and diversity of cognitive style. Our findings illustrate the utility of a “solution-oriented” approach to identifying principles of collective performance.
5 citations
TL;DR: This article explored a popular and important behavior that is frequently measured in public opinion surveys: news consumption and found that television news consumption is consistently overreported in surveys relative to passively collected behavioral data.
Abstract: Surveys are a vital tool for understanding public opinion and knowledge, but they can also yield biased estimates of behavior. Here we explore a popular and important behavior that is frequently measured in public opinion surveys: news consumption. Previous studies have shown that television news consumption is consistently overreported in surveys relative to passively collected behavioral data. We validate these earlier findings, showing that they continue to hold despite large shifts in news consumption habits over time, while also adding some new nuance regarding question wording. We extend these findings to survey reports of online and social media news consumption, with respect both to levels and trends. Third, we demonstrate the usefulness of passively collected data for measuring a quantity such as “consuming news” for which different researchers might reasonably choose different definitions. Finally, recognizing that passively collected data suffers from its own limitations, we outline a framework for using a mix of passively collected behavioral and survey-generated attitudinal data to accurately estimate consumption of news and related effects on public opinion and knowledge, conditional on media consumption.
4 citations