Duncan J. Watts's research while affiliated with University of Pennsylvania and other places

Publications (28)

Preprint
The dominant paradigm of experiments in the social and behavioral sciences views an experiment as a test of a theory, where the theory is assumed to generalize beyond the experiment’s specific conditions. According to this view, which Alan Newell once characterized as “playing twenty questions with nature,” theory is advanced one experiment at a ti...
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Partisan segregation within the news audience buffers many Americans from countervailing political views, posing a risk to democracy. Empirical studies of the online media ecosystem suggest that only a small minority of Americans, driven by a mix of demand and algorithms, are siloed according to their political ideology. However, such research omit...
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Addendum to HKS Misinformation Review “Research note: Examining potential bias in large-scale censored data” (https://doi.org/10.37016/mr-2020-74), published on July 26, 2021.
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Significance Informal political discussions with peers can increase trust in democracy and improve understanding of self and others. However, these benefits do not often materialize because people tend to shy away from political discussions and because friendship networks rarely expose highly divergent political views. In a large-scale experiment,...
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The standard experimental paradigm in the social, behavioral, and economic sciences is extremely limited. Although recent advances in digital technologies and crowdsourcing services allow individual experiments to be deployed and run faster than in traditional physical labs, a majority of experiments still focus on one-off results that do not gener...
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Significance Scientists and managers alike have been preoccupied with the question of whether and, if so, under what conditions groups of interacting problem solvers outperform autonomous individuals. Here we describe an experiment in which individuals and groups were evaluated on a series of tasks of varying complexity. We find that groups are as...
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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...
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Significance Daily share of news consumption on YouTube, a social media platform with more than 2 billion monthly users, has increased in the last few years. Constructing a large dataset of users’ trajectories across the full political spectrum during 2016–2019, we identify several distinct communities of news consumers, including “far-right” and “...
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We examine potential bias in Facebook’s 10-trillion cell URLs dataset, consisting of URLs shared on its platform and their engagement metrics. Despite the unprecedented size of the dataset, it was altered to protect user privacy in two ways: 1) by adding differentially private noise to engagement counts, and 2) by censoring the data with a 100-publ...
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Theories of organizations are sympathetic to long-standing ideas from network science that organizational networks should be regarded as multiscale and capable of displaying emergent properties. However, the historical difficulty of collecting individual-level network data for many (N ≫ 1) organizations, each of which comprises many (n ≫ 1) individ...
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Since the 2016 US presidential election, the deliberate spread of misinformation online, and on social media in particular, has generated extraordinary concern, in large part because of its potential effects on public opinion, political polarization, and ultimately democratic decision making. Recently, however, a handful of papers have argued that...
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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 e...
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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 con...
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Data sharing, research ethics, and incentives must improve
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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. Us...
Preprint
Full-text available
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 e...
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Full-text available
“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...
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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...
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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 ho...
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Across three studies that revealed the A/B Effect using a between-subjects design in Meyer et al. (2019), we find via corresponding within-subjects designs that the A/B Effect persists even when participants (1) have complete information about the options available to a decision-maker (i.e., to implement policy A for everyone or policy B for everyo...
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Randomized experiments have enormous potential to improve human welfare in many domains, including healthcare, education, finance, and public policy. However, such “A/B tests” are often criticized on ethical grounds even as similar, untested interventions are implemented without objection. We find robust evidence across 16 studies of 5,873 particip...
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Addressing fake news requires a multidisciplinary effort
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We propose to change the default P-value threshold for statistical significance for claims of new discoveries from 0.05 to 0.005.
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"We propose to change the default P-value threshold forstatistical significance for claims of new discoveries from 0.05 to 0.005."
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Over the past 100 years, social science has generated a tremendous number of theories on the topics of individual and collective human behaviour. However, it has been much less successful at reconciling the innumerable inconsistencies and contradictions among these competing explanations, a situation that has not been resolved by recent advances in...

Citations

... A consistent finding from recent research on harmful online behaviors is that they tend to be concentrated among a small number of individuals. Whether examining misinformation (Grinberg et al. 2019;Guess, Nagler, and Tucker 2019;Allen et al. 2020), radicalizing or partisan content (Hosseinmardi et al. 2021;Muise et al. 2022), or hate speech (Zannettou et al. 2020), a small number of individuals typically accounts for the vast majority of the behavior. Despite this statistical infrequency, the social consequences of such behaviors can be substantial, especially for people targeted by, or within the social networks of, the individuals perpetuating them. ...
... URLs that have been shared at least 100 times publicly are included in the first place. While this may be negligible when studying highly popular content and large user populations, it adds a hard-to-quantify uncertainty to understanding what happens with less popular outlets, especially in smaller countries like some of those in our sample (see also Allen et al., 2022). Similarly, the Gaussian noise in the data is especially problematic for studying the long tail of news dissemination. ...
... Balietti et al. [10] used informal political discussions with individuals sharing personal characteristics and social context to decrease polarization by exposing them to personal messages about a divisive political topic. According to the authors, friendship networks exhibit greater diversity of political views than is apparent to their members, and incidental conversations may expose interlocutors to diverse viewpoints. ...
... The relatively small size of this data implies that the noise added by differential privacy may make certain analyses impossible, which we verify in practice. Previous research on this dataset has also noted that its restriction to URLs shared only 100 times or more can significantly alter dataset metrics-a problem that is no doubt exacerbated in small, relatively low-volume URL samples (Allen et al. 2021). Thus, our analysis here today is novel in that it is an attempt to use a social media dataset obscured by differential privacy to analyze behavior around a single narrative, rather than behavior in general. ...
... Despite the recent evolution of the epistemological trends discussed above, creativity research has seldom appreciated the extent to which distributed interaction properties play a role in creative processes (Kurtzberg and Amabile, 2001;Lebuda et al., 2016;Almaatouq et al., 2021). Instead, ideas are still most often thought to be born out of individual minds before they reach the world, and therefore others (Wheeler, 2018). ...
... In this work, we follow the definition of echo chambers provided in [6] to understand the users' attention patterns on YouTube during the COVID-19 pandemic. According to some studies, YouTube is playing a prominent role in the radicalization of opinions [10,25,26] and in the diffusion of questionable (i.e., poorly fact-checked) content being one of the most visited online domain and information retrieval platforms. Our dataset contains 10M comments relative to the videos published from 68 prominent information channels on YouTube in a period ranging from December 2019 to September 2020. ...
... Most prior studies focused on understanding the algorithms that promote hate ideology content [1,15] or the user interactions with hate ideology videos [7,8]. Studies have examined hate groups on other social media [13,16]. ...
... Archival users vary in their familiarity with technological solutions, with Talboom and Underdown (2019) categorising users of digital collection into three broad types, arrayed in terms of their level of digital engagement: (1) "readers", who want to access a digital source like a traditional paper source; (2) "digitally curious", who want to search large databases to identify items of importance for more in-depth study; and finally, (3) "data users", who want to perform computational analysis over entire collections. And while there are some solutions available for groups 1 and 3 (reproduction of digital items where these can be released and access to a large-scale database for computational, nonconsumptive use, respectively), there are currently no tools or access options for users in group 2. However, it is likely that many future users will fall into this category, replacing or converting the "readers", while the "data users" are likely to move on to ever bigger and more diverse data sets that continue to push the boundaries of "big data" computational analysis (see Jacobs and Watts 2021). ...
... This research investigated the propagation of the QAnon narrative based on, to the best of our knowledge, the most extensive dataset about the conspiracy theory on Facebook. Scholars have pointed out the need to understand the ecosystem in which disinformation is produced and propagated within and across online platforms [20,37,59,61,64,70]. The QAnon conspiracy theory is known to encourage its audience to assemble and remix different pieces of information [70], so it is even more crucial to examine how online communities discussing QAnon interacted with the broader ecosystem by drawing information from various sources to construct and support their narratives. ...
... The study was approved by the Ethics Committee of the Max Planck Institute for Human Development. The game was implemented in Empirica [33]. The game's task consisted in predicting a binary weather outcome (Rain vs. ...