A5002033007- Opinion Dynamics and Social Influence
- Misinformation and Its Impacts
- Complex Network Analysis Techniques
- Hate Speech and Cyberbullying Detection
- Terrorism, Counterterrorism, and Political Violence
- Social Media and Politics
- Vaccine Coverage and Hesitancy
- International Relations in Latin America
- Media Influence and Politics
- Public Relations and Crisis Communication
- Innovation Diffusion and Forecasting
- Mathematical and Theoretical Epidemiology and Ecology Models
- International Development and Aid
- Evolutionary Game Theory and Cooperation
- Landslides and related hazards
- COVID-19 epidemiological studies
- Spam and Phishing Detection
- HIV, Drug Use, Sexual Risk
- Flood Risk Assessment and Management
- Hydrology and Sediment Transport Processes
- Youth, Politics, and Society
- Crime Patterns and Interventions
- HIV/AIDS oral health manifestations
- Network Security and Intrusion Detection
- SARS-CoV-2 and COVID-19 Research
University of Iowa
2024
George Washington University
2019-2023
University of Maryland, College Park
2020
University of Miami
2013-2016
Hôpital Tenon
2014
Sorbonne Université
2014
A huge amount of potentially dangerous COVID-19 misinformation is appearing online. Here we use machine learning to quantify content among online opponents establishment health guidance, in particular vaccinations ("anti-vax"). We find that the anti-vax community developing a less focused debate around than its counterpart, pro-vaccination ("pro-vax") community. However, exhibits broader range "flavors" topics, and hence can appeal cross-section individuals seeking guidance online, e.g. wary...
Support for an extremist entity such as Islamic State (ISIS) somehow manages to survive globally online despite considerable external pressure and may ultimately inspire acts by individuals having no history of extremism, membership in a terrorist faction, or direct links leadership. Examining longitudinal records activity, we uncovered ecology evolving on daily time scale that drives support, provide mathematical theory describes it. The features self-organized aggregates (ad hoc groups...
Online hate speech is a critical and worsening problem, with extremists using social media platforms to radicalize recruits coordinate offline violent events. While much progress has been made in analyzing online speech, no study date classified multiple types of across both mainstream fringe platforms. We conduct supervised machine learning analysis 7 on 6 interconnected find that trigger events, such as protests elections, are often followed by increases bear seemingly little connection...
Abstract We show that malicious COVID-19 content, including racism, disinformation, and misinformation, exploits the multiverse of online hate to spread quickly beyond control any individual social media platform. provide a first mapping network across six major platforms. demonstrate how content can travel this in ways subvert platform moderation efforts. Machine learning topic analysis shows quantitatively communities are sharpening as weapon, with topics evolving rapidly becoming...
Objectives. To understand changes in how Facebook pages frame vaccine opposition. Methods. We categorized 204 expressing opposition, extracting public posts through November 20, 2019. analyzed from October 2009 2019 to examine if pages’ content was coalescing. Results. Activity promoting choice as a civil liberty increased January 2015, April 2016, and (t[76] = 11.33 [P < .001]; t[46] 7.88 t[41] 17.27 .001], respectively). The increase strongest mentioning US states (t[41] 19.06; P .001)....
We show that malicious COVID-19 content, including hate speech, disinformation, and misinformation, exploits the multiverse of online to spread quickly beyond control any individual social media platform. Machine learning topic analysis shows quantitatively how communities are weaponizing COVID-19, with topics evolving rapidly content becoming increasingly coherent. Our mathematical provides a generalized form public health R0 predicting tipping point for multiverse-wide viral spreading,...
Many high-profile societal problems involve an individual or group repeatedly attacking another - from child-parent disputes, sexual violence against women, civil unrest, violent conflicts and acts of terror, to current cyber-attacks on national infrastructure ultrafast cyber-trades stockholders. There is urgent need quantify the likely severity timing such future acts, shed light perpetrators, identify intervention strategies. Here we present a combined analysis multiple datasets across all...
Open Source Indicators (OSI) such as Google Trends (GT) promise to uncover the social dynamics associated with behavior that precede episodes of civil unrest. There are myriad reasons why societies may become unstable: Our analysis does not require or inquire underlying for discontent but instead takes into account differences variegated contexts. This paper examines instances this volatile and suggests a simple model predicting unrest events using GT an open source indicator (OSI). It...
Abstract We show that malicious COVID-19 content, including racism, disinformation, and misinformation, exploits the multiverse of online hate to spread quickly beyond control any individual social media platform. provide a first mapping network across six major platforms. demonstrate how content can travel this in ways subvert platform moderation efforts. Machine learning topic analysis shows quantitatively communities are sharpening as weapon, with topics evolving rapidly becoming...
This Resource Letter provides a guide into the literature on modeling and explaining political conflict, violence, wars. Although this is dominated by social scientists, multidisciplinary work currently being developed in wake of myriad methodological approaches that have sought to analyze predict violence. The works covered herein present an overview abundance approaches. Since there variety possible data sets theoretical approaches, level detail scope models can vary quite considerably....
Abstract We quantify how and when extreme subpopulations emerge in a model society despite everyone having the same information available resources – show that counterintuitively these extremes will likely be enhanced over time by new social media algorithms designed to reduce division. verify our analysis mathematically, it reproduces (a) time-dependent behavior observed controlled experiments on humans, (b) findings of recent study online Facebook concerning impact ‘soft’ ‘hard’ news, (c)...
Abstract Disrupting the emergence and evolution of potentially violent online extremist movements is a crucial challenge. Extremism research has analyzed such in detail, focusing on individual- movement-level characteristics. But are there system-level commonalities ways these emerge grow? Here we compare growth Boogaloos, new increasingly prominent U.S. movement, to support for ISIS, militant, terrorist organization based Middle East that follows radical version Islam. We show early...
Many governments have managed to control their COVID-19 outbreak with a simple message: keep the effective '$R$ number' $R<1$ prevent widespread contagion and flatten curve. This raises question whether similar policy could dangerous online 'infodemics' of information, misinformation disinformation. Here we show, using multi-platform data from infodemic, that its spreading instead encompasses different dynamical regime where communities users within across independent platforms,...
From the moment first COVID-19 vaccines are rolled out, there will need to be a large fraction of global population ready in line. It is therefore crucial start managing growing hesitancy any such vaccine. The current approach trying convince "no"s cannot work quickly enough, nor can policy find, remove and/or rebut all individual pieces COVID and vaccine misinformation. Instead, we show how this done simpler way by moving away from chasing misinformation content focusing instead on...
We present a many-body theory that explains and reproduces recent observations of population polarization dynamics, is supported by controlled human experiments, addresses the controversy surrounding Internet's impact. It predicts whether how becomes polarized dictated nature underlying competition, rather than validity information individuals receive or their online bubbles. Building on this framework, we show next-generation social media algorithms aimed at pulling people together, will...
Abstract Significant errors often arise when measuring streamflow during high flows and flood events. Such conflated by short records of observations may induce bias in the frequency estimates, leading to costly engineering design mistakes. This work illustrates how observational (measurement) affect uncertainty estimation. The study used Bulletin 17C (US standard) method estimate frequencies historical peak modified represent measurement limitations. To perform modifications, authors...
Online social media allows individuals to cluster around common interests - including hate. We show that tight-knit clusters interlink form resilient 'global hate highways' bridge independent network platforms, countries, languages and ideologies, can quickly self-repair rewire. provide a mathematical theory reveals hidden resilience in the global axis of hate; explains likely ineffectiveness current control methods; offers improvements. Our results reveal new science for...
We present preliminary results on the online war surrounding distrust of expertise in medical science -- specifically, issue vaccinations. While and misinformation politics can damage democratic elections, context it may also endanger lives through missed vaccinations DIY cancer cures. find that this health has evolved into a highly efficient network insurgency with direct inter-crowd links across countries, continents cultures. The anti-vax crowds (referred to as Red) now appear better...
We show that the eclectic "Boogaloo" extremist movement is now rising to prominence in U.S., has a hidden online mathematical order identical ISIS during its early development, despite their stark ideological, geographical and cultural differences. The evolution of each across scales follows single shockwave equation accounts for individual heterogeneity interactions. This predicts how disrupt onset 'flatten curve' such extremism by nudging collective chemistry.
Abstract Parents - particularly moms increasingly consult social media for support when taking decisions about their young children, and likely also advising other family members such as elderly relatives. Minimizing malignant online influences is therefore crucial to securing assent policies ranging from vaccinations, masks distancing against the pandemic, household best practices climate change, acceptance of future 5G towers nearby. Here we show how a strengthening bonds across...