Social media have been proposed as a data source for influenza surveillance because they have the potential to offer real-time access to millions of short, geographically localized messages ...containing information regarding personal well-being. However, accuracy of social media surveillance systems declines with media attention because media attention increases "chatter" - messages that are about influenza but that do not pertain to an actual infection - masking signs of true influenza prevalence. This paper summarizes our recently developed influenza infection detection algorithm that automatically distinguishes relevant tweets from other chatter, and we describe our current influenza surveillance system which was actively deployed during the full 2012-2013 influenza season. Our objective was to analyze the performance of this system during the most recent 2012-2013 influenza season and to analyze the performance at multiple levels of geographic granularity, unlike past studies that focused on national or regional surveillance. Our system's influenza prevalence estimates were strongly correlated with surveillance data from the Centers for Disease Control and Prevention for the United States (r = 0.93, p < 0.001) as well as surveillance data from the Department of Health and Mental Hygiene of New York City (r = 0.88, p < 0.001). Our system detected the weekly change in direction (increasing or decreasing) of influenza prevalence with 85% accuracy, a nearly twofold increase over a simpler model, demonstrating the utility of explicitly distinguishing infection tweets from other chatter.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
To understand how Twitter bots and trolls ("bots") promote online health content.
We compared bots' to average users' rates of vaccine-relevant messages, which we collected online from July 2014 ...through September 2017. We estimated the likelihood that users were bots, comparing proportions of polarized and antivaccine tweets across user types. We conducted a content analysis of a Twitter hashtag associated with Russian troll activity.
Compared with average users, Russian trolls (χ
(1) = 102.0; P < .001), sophisticated bots (χ
(1) = 28.6; P < .001), and "content polluters" (χ
(1) = 7.0; P < .001) tweeted about vaccination at higher rates. Whereas content polluters posted more antivaccine content (χ
(1) = 11.18; P < .001), Russian trolls amplified both sides. Unidentifiable accounts were more polarized (χ
(1) = 12.1; P < .001) and antivaccine (χ
(1) = 35.9; P < .001). Analysis of the Russian troll hashtag showed that its messages were more political and divisive.
Whereas bots that spread malware and unsolicited content disseminated antivaccine messages, Russian trolls promoted discord. Accounts masquerading as legitimate users create false equivalency, eroding public consensus on vaccination. Public Health Implications. Directly confronting vaccine skeptics enables bots to legitimize the vaccine debate. More research is needed to determine how best to combat bot-driven content.
The COVID-19 pandemic demonstrated the importance of social distancing practices to stem the spread of the virus. However, compliance with public health guidelines was mixed. Understanding what ...factors are associated with differences in compliance can improve public health messaging since messages could be targeted and tailored to different population segments. We utilize Twitter data on social mobility during COVID-19 to reveal which populations practiced social distancing and what factors correlated with this practice. We analyze correlations between demographic and political affiliation with reductions in physical mobility measured by public geolocation tweets. We find significant differences in mobility reduction between these groups in the United States. We observe that males, Asian and Latinx individuals, older individuals, Democrats, and people from higher population density states exhibited larger reductions in movement. Furthermore, our study also unveils meaningful insights into the interactions between different groups. We hope these findings will provide evidence to support public health policy-making.
The COVID-19 pandemic brought widespread attention to an "infodemic" of potential health misinformation. This claim has not been assessed based on evidence. We evaluated if health misinformation ...became more common during the pandemic. We gathered about 325 million posts sharing URLs from Twitter and Facebook during the beginning of the pandemic (March 8-May 1, 2020) compared to the same period in 2019. We relied on source credibility as an accepted proxy for misinformation across this database. Human annotators also coded a subsample of 3000 posts with URLs for misinformation. Posts about COVID-19 were 0.37 times as likely to link to "not credible" sources and 1.13 times more likely to link to "more credible" sources than prior to the pandemic. Posts linking to "not credible" sources were 3.67 times more likely to include misinformation compared to posts from "more credible" sources. Thus, during the earliest stages of the pandemic, when claims of an infodemic emerged, social media contained proportionally less misinformation than expected based on the prior year. Our results suggest that widespread health misinformation is not unique to COVID-19. Rather, it is a systemic feature of online health communication that can adversely impact public health behaviors and must therefore be addressed.
Celotno besedilo
Dostopno za:
DOBA, IZUM, KILJ, NUK, PILJ, PNG, SAZU, SIK, UILJ, UKNU, UL, UM, UPUK
Faculty diversity is a longstanding challenge in the US. However, we lack a quantitative and systemic understanding of how the career transitions into assistant professor positions of PhD scientists ...from underrepresented minority (URM) and well-represented (WR) racial/ethnic backgrounds compare. Between 1980 and 2013, the number of PhD graduates from URM backgrounds increased by a factor of 9.3, compared with a 2.6-fold increase in the number of PhD graduates from WR groups. However, the number of scientists from URM backgrounds hired as assistant professors in medical school basic science departments was not related to the number of potential candidates (R
=0.12, p>0.07), whereas there was a strong correlation between these two numbers for scientists from WR backgrounds (R
=0.48, p<0.0001). We built and validated a conceptual system dynamics model based on these data that explained 79% of the variance in the hiring of assistant professors and posited no hiring discrimination. Simulations show that, given current transition rates of scientists from URM backgrounds to faculty positions, faculty diversity would not increase significantly through the year 2080 even in the context of an exponential growth in the population of PhD graduates from URM backgrounds, or significant increases in the number of faculty positions. Instead, the simulations showed that diversity increased as more postdoctoral candidates from URM backgrounds transitioned onto the market and were hired.
Influence operations are large-scale efforts to manipulate public opinion. The rapid detection and disruption of these operations is critical for healthy public discourse. Emergent AI technologies ...may enable novel operations that evade detection and influence public discourse on social media with greater scale, reach, and specificity. New methods of detection with inductive learning capacity will be needed to identify novel operations before they indelibly alter public opinion and events. To this end, we develop an inductive learning framework that: (1) determines content- and graph-based indicators that are not specific to any operation; (2) uses graph learning to encode abstract signatures of coordinated manipulation; and (3) evaluates generalization capacity by training and testing models across operations originating from Russia, China, and Iran. We find that this framework enables strong cross-operation generalization while also revealing salient indicators-illustrating a generic approach which directly complements transductive methodologies, thereby enhancing detection coverage.
We present the first Ge-based constraints on sub-MeV /c2 dark matter (DM) particles interacting with electrons using a 33.4 g Ge cryogenic detector with a 0.53 electron-hole pair (rms) resolution, ...operated underground at the Laboratoire Souterrain de Modane. Competitive constraints are set on the DM-electron scattering cross section, as well as on the kinetic mixing parameter of dark photons down to 1 eV / c2. In particular, the most stringent limits are set for dark photon DM in the 6 to 9 eV / c2 range. These results demonstrate the high relevance of Ge cryogenic detectors for the search of DM-induced eV-scale electron signals.
Abstract
Anti-vaccine content and other kinds of misinformation are hypothesized to be more heavily monetized than other kinds of online content. We test this hypothesis by applying several novel and ...scalable measures of website monetization strategies to more than 400,000 links shared by 261 anti-vaccine Facebook pages and 190 pro-vaccine ones. Contrary to expectations, websites promoted in pro-vaccine venues do more to monetize attention than those promoted in anti-vaccine venues. This is a consequence of how intensely monetized news websites are—pro-vaccine venues share more links to news. The specific news sites shared by anti-vaccine venues are rated less credible by fact-checking organizations, but we find little substantive difference in their monetization strategies. These results emphasize the need to interpret measures of monetization within the context of the broader “attention economy”.
A method is presented to determine the field dependence of the intervalley scattering rate for hot electrons in germanium, based on an analysis of electron straggle in a detector crystal fitted with ...segmented electrodes. Measurements in high-purity and in lightly doped n- and p-type crystals at millikelvin temperatures demonstrate the dominant role of impurity scattering at low field (
<
∼
a few V/cm), whereas phonon scattering takes precedence at higher field intensities. An analysis of the experimental data by reference to past investigations of the acoustoelectric effect in germanium strongly suggests that the impurities involved are the dopant species in the neutral state.
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