rvenkat + ?   132

[1801.07351] Tracking network dynamics: a survey of distances and similarity metrics
From longitudinal biomedical studies to social networks, graphs have emerged as a powerful framework for describing evolving interactions between agents in complex systems. In such studies, after pre-processing, the data can be represented by a set of graphs, each representing a system's state at different points in time. The analysis of the system's dynamics depends on the selection of the appropriate analytical tools. After characterizing similarities between states, a critical step lies in the choice of a distance between graphs capable of reflecting such similarities. While the literature offers a number of distances that one could a priori choose from, their properties have been little investigated and no guidelines regarding the choice of such a distance have yet been provided. In particular, most graph distances consider that the nodes are exchangeable and do not take into account node identities. Accounting for the alignment of the graphs enables us to enhance these distances' sensitivity to perturbations in the network and detect important changes in graph dynamics. Thus the selection of an adequate metric is a decisive --yet delicate--practical matter.
In the spirit of Goldenberg, Zheng and Fienberg's seminal 2009 review, the purpose of this article is to provide an overview of commonly-used graph distances and an explicit characterization of the structural changes that they are best able to capture. We use as a guiding thread to our discussion the application of these distances to the analysis of both a longitudinal microbiome dataset and a brain fMRI study. We show examples of using permutation tests to detect the effect of covariates on the graphs' variability. Synthetic examples provide intuition as to the qualities and drawbacks of the different distances. Above all, we provide some guidance for choosing one distance over another in certain types of applications.
temporal_networks  review  network_data_analysis  teaching  ?  for_friends 
5 weeks ago by rvenkat
Structure and dynamical behavior of non-normal networks | Science Advances
We analyze a collection of empirical networks in a wide spectrum of disciplines and show that strong non-normality is ubiquitous in network science. Dynamical processes evolving on non-normal networks exhibit a peculiar behavior, as initial small disturbances may undergo a transient phase and be strongly amplified in linearly stable systems. In addition, eigenvalues may become extremely sensible to noise and have a diminished physical meaning. We identify structural properties of networks that are associated with non-normality and propose simple models to generate networks with a tunable level of non-normality. We also show the potential use of a variety of metrics capturing different aspects of non-normality and propose their potential use in the context of the stability of complex ecosystems.

Also here
networks  linear_algebra  dynamical_system  network_data_analysis  teaching  ? 
5 weeks ago by rvenkat
The Unfavorable Economics of Measuring the Returns to Advertising * | The Quarterly Journal of Economics | Oxford Academic
Twenty-five large field experiments with major U.S. retailers and brokerages, most reaching millions of customers and collectively representing $2.8 million in digital advertising expenditure, reveal that measuring the returns to advertising is difficult. The median confidence interval on return on investment is over 100 percentage points wide. Detailed sales data show that relative to the per capita cost of the advertising, individual-level sales are very volatile; a coefficient of variation of 10 is common. Hence, informative advertising experiments can easily require more than 10 million person-weeks, making experiments costly and potentially infeasible for many firms. Despite these unfavorable economics, randomized control trials represent progress by injecting new, unbiased information into the market. The inference challenges revealed in the field experiments also show that selection bias, due to the targeted nature of advertising, is a crippling concern for widely employed observational methods.


--Stupid question: If returns on advertising are hard to measure. Doesn't this make all the fuss about influence of disinformation campaigns in 2016 a bit of an overreaction? Or is it that the general results of this paper are not applicable in general settings when the ads are disguised as opinions of actual people?
economics  computaional_advertising  online_experiments  intervention  causal_inference  ?  via:randw  debates 
7 weeks ago by rvenkat
A state variable for crumpled thin sheets | Communications Physics
Despite the apparent ease with which sheets of paper are crumpled and tossed away, crumpling dynamics are often considered a paradigm of complexity. This arises from the infinite number of configurations that disordered, crumpled sheets can take. Here we experimentally show that key aspects of axially confined crumpled Mylar sheets have a very simple description; evolution of damage in crumpling dynamics can largely be described by a single global quantity—the total length of creases. We follow the evolution of the damage network in repetitively crumpled elastoplastic sheets, and show that the dynamics are deterministic, depending only on the instantaneous state of the crease network and not on the crumpling history. We also show that this global quantity captures the crumpling dynamics of a sheet crumpled for the first time. This leads to a remarkable reduction in complexity, allowing a description of a highly disordered system by a single state parameter.

-- I know what I'll do when someone throws *it's must be a complex systems* argument at me.
physics  fun  complexity  ?  teaching  philosophy_of_science 
8 weeks ago by rvenkat
Modeling Asymmetric Relationships from Symmetric Networks | Political Analysis | Cambridge Core
Many bilateral relationships requiring mutual agreement produce observable networks that are symmetric (undirected). However, the unobserved, asymmetric (directed) network is frequently the object of scientific interest. We propose a method that probabilistically reconstructs the latent, asymmetric network from the observed, symmetric graph in a regression-based framework. We apply this model to the bilateral investment treaty network. Our approach successfully recovers the true data generating process in simulation studies, extracts new, politically relevant information about the network structure inaccessible to alternative approaches, and has superior predictive performance.

-- latent preference structure is used to infer directionality of edges. But is causal reasoning involved in inferring directionality?
networks  network_data_analysis  international_affairs  causal_inference  ? 
9 weeks ago by rvenkat
Input–output maps are strongly biased towards simple outputs | Nature Communications
Many systems in nature can be described using discrete input–output maps. Without knowing details about a map, there may seem to be no a priori reason to expect that a randomly chosen input would be more likely to generate one output over another. Here, by extending fundamental results from algorithmic information theory, we show instead that for many real-world maps, the a priori probability P(x) that randomly sampled inputs generate a particular output x decays exponentially with the approximate Kolmogorov complexity 𝐾̃ (𝑥) of that output. These input–output maps are biased towards simplicity. We derive an upper bound P(x) ≲ 2−𝑎𝐾̃ (𝑥)−𝑏, which is tight for most inputs. The constants a and b, as well as many properties of P(x), can be predicted with minimal knowledge of the map. We explore this strong bias towards simple outputs in systems ranging from the folding of RNA secondary structures to systems of coupled ordinary differential equations to a stochastic financial trading model.

--interesting but cannot understand the buzz around this paper.
complexity  information_theory  algorithms  macro_from_micro  ? 
10 weeks ago by rvenkat
The Theory Is Predictive, but Is It Complete? An Application to Human Perception of Randomness by Jon Kleinberg, Annie Liang, Sendhil Mullainathan :: SSRN
When testing a theory, we should ask not just whether its predictions match what we see in the data, but also about its “completeness”: how much of the predictable variation in the data does the theory capture? Defining completeness is conceptually challenging, but we show how methods based on machine learning can provide tractable measures of completeness. We also identify a model domain—the human perception and generation of randomness — where measures of completeness can be feasibly analyzed; from these measures we discover there is significant structure in the problem that existing theories have yet to capture.

-- I can think of other domains (e.g. neuroscience, cosmology, behavioral genetics?) where such analysis might be possible. Also, I am curious if philosophers of science (and statistics) have discussed anything similar or _superior_.
randomness  statistics  machine_learning  prediction  model_selection  ?  cognitive_science  sendhil.mullainathan 
september 2018 by rvenkat
The Explanatory Power of Network Models | Philosophy of Science: Vol 83, No 5
Network analysis is increasingly used to discover and represent the organization of complex systems. Focusing on examples from neuroscience in particular, I argue that whether network models explain, how they explain, and how much they explain cannot be answered for network models generally but must be answered by specifying an explanandum, by addressing how the model is applied to the system, and by specifying which kinds of relations count as explanatory.
philosophy_of_science  neuroscience  connectome  social_networks  ? 
september 2018 by rvenkat
Fanning the Flames of Hate: Social Media and Hate Crime by Karsten Müller, Carlo Schwarz :: SSRN
This paper investigates the link between social media and hate crime using Facebook data. We study the case of Germany, where the recently emerged right-wing party Alternative für Deutschland (AfD) has developed a major social media presence. We show that right-wing anti-refugee sentiment on Facebook predicts violent crimes against refugees in otherwise similar municipalities with higher social media usage. To further establish causality, we exploit exogenous variation in major internet and Facebook outages, which fully undo the correlation between social media and hate crime. We further find that the effect decreases with distracting news events; increases with user network interactions; and does not hold for posts unrelated to refugees. Our results suggest that social media can act as a propagation mechanism between online hate speech and real-life violent crime.
media_studies  social_influence  platform_studies  violence  mediation_analysis  ?  causal_inference  i_remain_skeptical 
august 2018 by rvenkat
[1705.02801] Graph Embedding Techniques, Applications, and Performance: A Survey
Graphs, such as social networks, word co-occurrence networks, and communication networks, occur naturally in various real-world applications. Analyzing them yields insight into the structure of society, language, and different patterns of communication. Many approaches have been proposed to perform the analysis. Recently, methods which use the representation of graph nodes in vector space have gained traction from the research community. In this survey, we provide a comprehensive and structured analysis of various graph embedding techniques proposed in the literature. We first introduce the embedding task and its challenges such as scalability, choice of dimensionality, and features to be preserved, and their possible solutions. We then present three categories of approaches based on factorization methods, random walks, and deep learning, with examples of representative algorithms in each category and analysis of their performance on various tasks. We evaluate these state-of-the-art methods on a few common datasets and compare their performance against one another. Our analysis concludes by suggesting some potential applications and future directions. We finally present the open-source Python library we developed, named GEM (Graph Embedding Methods, available at this https URL), which provides all presented algorithms within a unified interface to foster and facilitate research on the topic.

--Ok as a survey. Works from the following definition of graph embedding.

(Graph embedding) Given a graph G=(V,E),a graph embedding is a mapping f:vi→yi∈Rd∀∈[n]such that d |V |and the function f preserves some proximity measure defined on graph G
graph_theory  survey  geometry  topological_data_analysis  networks  ? 
august 2018 by rvenkat
[1711.04024] How fragile are information cascades?
It is well known that sequential decision making may lead to information cascades. That is, when agents make decisions based on their private information, as well as observing the actions of those before them, then it might be rational to ignore their private signal and imitate the action of previous individuals. If the individuals are choosing between a right and a wrong state, and the initial actions are wrong, then the whole cascade will be wrong. This issue is due to the fact that cascades can be based on very little information.
We show that if agents occasionally disregard the actions of others and base their action only on their private information, then wrong cascades can be avoided. Moreover, we study the optimal asymptotic rate at which the error probability at time t can go to zero. The optimal policy is for the player at time t to follow their private information with probability pt=c/t, leading to a learning rate of c′/t, where the constants c and c′ are explicit.
self_organization  information_diffusion  contagion  decision_making  models_of_behavior  networks  ? 
june 2018 by rvenkat
[1803.09123] Equation Embeddings
We present an unsupervised approach for discovering semantic representations of mathematical equations. Equations are challenging to analyze because each is unique, or nearly unique. Our method, which we call equation embeddings, finds good representations of equations by using the representations of their surrounding words. We used equation embeddings to analyze four collections of scientific articles from the arXiv, covering four computer science domains (NLP, IR, AI, and ML) and ∼98.5k equations. Quantitatively, we found that equation embeddings provide better models when compared to existing word embedding approaches. Qualitatively, we found that equation embeddings provide coherent semantic representations of equations and can capture semantic similarity to other equations and to words.

--Seems like a good first step but feels like a reinvention of some of the work by Simon and Langley from a M.I. Jordan perspective.
machine_learning  science_of_science  scientometry  ?  natural_language_processing  david.blei 
april 2018 by rvenkat
Imagine you woke up one morning, and everything that engineers had created disappeared. What would you see?

No cars, no houses; no phones, bridges or roads. No tunnels under tidal rivers, no soaring skyscrapers. Engineering is an intrinsic and intimate part of our existence, shaping the spaces in which reside. We cannot live without it.

In BUILT, structural engineer Roma Agrawal takes a unique look at how construction has evolved from the mud huts of our ancestors to towers of steel that reach into the sky. She unearths how humans have tunnelled through kilometres of solid mountain, bridged the widest and deepest of rivers, and tamed Nature’s precious – and elusive – water resources. She tells vivid tales of the pioneers behind landmark builds such as the Brooklyn Bridge and the Burj Khalifa, and examines, from an engineering perspective, tragedies like the collapse of the Twin Towers. She reveals how she designs a building so it will stand strong – even in the face of gales, fire, earthquakes and explosions.

With colourful stories of her life-long fascination with buildings – and her own hand-drawn illustrations – Roma uncovers the extraordinary secret lives of structures.
book  engineering  design  philosophy_of_technology  ? 
march 2018 by rvenkat
[1706.00394] Multiscale unfolding of real networks by geometric renormalization
Multiple scales coexist in complex networks. However, the small world property makes them strongly entangled. This turns the elucidation of length scales and symmetries a defiant challenge. Here, we define a geometric renormalization group for complex networks and use the technique to investigate networks as viewed at different scales. We find that real networks embedded in a hidden metric space show geometric scaling, in agreement with the renormalizability of the underlying geometric model. This allows us to unfold real scale-free networks in a self-similar multilayer shell which unveils the coexisting scales and their interplay. The multiscale unfolding offers a basis for a new approach to explore critical phenomena and universality in complex networks, and affords us immediate practical applications, like high-fidelity smaller-scale replicas of large networks and a multiscale navigation protocol in hyperbolic space which boosts the success of single-layer versions.
networks  hyperbolic_geometry  phase_transition  renormalization  network_data_analysis  ? 
march 2018 by rvenkat
Why French Kids Don't Have ADHD | Psychology Today
In the United States, at least 9 percent of school-aged children have been diagnosed with ADHD, and are taking pharmaceutical medications. In France, the percentage of kids diagnosed and medicated for ADHD is less than .5 percent. How has the epidemic of ADHD—firmly established in the U.S.—almost completely passed over children in France?

-- where did they get this number from?
-- also interesting is the fact that France has its version of DSM
-- The rest of the article is pretty preachy and redundant
social_psychology  DSM  comparative  evolutionary_psychology  ?  via:?  track_down_references 
march 2018 by rvenkat
Monophily in social networks introduces similarity among friends-of-friends | Nature Human Behaviour
The observation that individuals tend to be friends with people who are similar to themselves, commonly known as homophily, is a prominent feature of social networks. While homophily describes a bias in attribute preferences for similar others, it gives limited attention to variability. Here, we observe that attribute preferences can exhibit variation beyond what can be explained by homophily. We call this excess variation monophily to describe the presence of individuals with extreme preferences for a particular attribute possibly unrelated to their own attribute. We observe that monophily can induce a similarity among friends-of-friends without requiring any similarity among friends. To simulate homophily and monophily in synthetic networks, we propose an overdispersed extension of the classical stochastic block model. We use this model to demonstrate how homophily-based methods for predicting attributes on social networks based on friends (that is, 'the company you keep') are fundamentally different from monophily-based methods based on friends-of-friends (that is, 'the company you’re kept in'). We place particular focus on predicting gender, where homophily can be weak or non-existent in practice. These findings offer an alternative perspective on network structure and prediction, complicating the already difficult task of protecting privacy on social networks.

social_networks  privacy  network_data_analysis  latent_variable  block_model  via:clauset  networks  teaching  ? 
march 2018 by rvenkat
[1803.04755] Detecting sequences of system states in temporal networks
Many time-evolving systems in nature, society and technology leave traces of the interactions within them. These interactions form temporal networks that reflect the states of the systems. In this work, we pursue a coarse-grained description of these systems by proposing a method to assign discrete states to the systems and inferring the sequence of such states from the data. Such states could, for example, correspond to a mental state (as inferred from neuroimaging data) or the operational state of an organization (as inferred by interpersonal communication). Our method combines a graph distance measure and hierarchical clustering. Using several empirical data sets of social temporal networks, we show that our method is capable of inferring the system's states such as distinct activities in a school and a weekday state as opposed to a weekend state. We expect the methods to be equally useful in other settings such as temporally varying protein interactions, ecological interspecific interactions, functional connectivity in the brain and adaptive social networks.
networks  temporal_networks  time_series  interating_particle_system  ? 
march 2018 by rvenkat
SocArXiv Papers | Too Many Papers? Slowed Canonical Progress in Large Fields of Science
We argue that paradigmatic progress may be slowed as scientific fields grow large. This assertion is supported by evidence from citation patterns across 251 fields—over 1 billion citations among 57 million papers over 54 years—covered by the Web of Science dataset. A deluge of papers in a scientific field does not lead to quick turnover of central ideas, but rather to the ossification of canon.
bibliometry  scientometry  science_as_a_social_process  scientific_publishing_complex  market_failures  ?  via:? 
march 2018 by rvenkat
Wealth, Slave Ownership, and Fighting for the Confederacy: An Empirical Study of the American Civil War
How did personal wealth affect the likelihood southerners fought for the Confederate Army in the American Civil War? We offer competing accounts for how we should expect individual wealth, in the form of land, and atrociously, in slaves, to affect white men’s decisions to join the Confederate Army. We assemble a dataset on roughly 3.9 million white citizens in Confederate states, and we show that slaveowners were more likely to fight in the Confederate Army than non-slaveowners. To see if these links are causal, we exploit a randomized land lottery in 19th-century Georgia. Households of lottery winners owned more slaves in 1850 and were more likely to have sons who fought in the Confederate Army than were households who did not win the lottery. Our results suggest that for wealthy southerners, the stakes associated with the conflict’s threat to end the institution of slavery overrode the incentives to free-ride and to avoid paying the costs of war

-- very, very counterintuitive to my worldview. Interesting if these results hold up in other conflicts. Anybody studying demographics of East India Company or the subsequent British Army?
economic_history  political_sociology  causal_inference  rational_choice  slavery  civil_war  united_states_of_america  19th_century  dmce  teaching  ?  via:nyhan 
february 2018 by rvenkat
[1802.00048] Deceptive Games
Deceptive games are games where the reward structure or other aspects of the game are designed to lead the agent away from a globally optimal policy. While many games are already deceptive to some extent, we designed a series of games in the Video Game Description Language (VGDL) implementing specific types of deception, classified by the cognitive biases they exploit. VGDL games can be run in the General Video Game Artificial Intelligence (GVGAI) Framework, making it possible to test a variety of existing AI agents that have been submitted to the GVGAI Competition on these deceptive games. Our results show that all tested agents are vulnerable to several kinds of deception, but that different agents have different weaknesses. This suggests that we can use deception to understand the capabilities of a game-playing algorithm, and game-playing algorithms to characterize the deception displayed by a game.
artificial_intelligence  adversarial_examples  ?  via:zeynep 
february 2018 by rvenkat
The New Conspiracists | Dissent Magazine
--misleading title, the article is more about use of disinformation, conspiratorial factoids with the dismantling of democratic institutions and administrative state in mind.
dissent_mag  administrative_state  institutions  conspiracy_theories  epidemiology_of_representations  political_psychology  cultural_cognition  dmce  networks  teaching  ? 
january 2018 by rvenkat
Platform Capitalism | Critical Theory | Continental Philosophy | General Philosophy | Subjects | Wiley
What unites Google and Facebook, Apple and Microsoft, Siemens and GE, Uber and Airbnb? Across a wide range of sectors, these firms are transforming themselves into platforms: businesses that provide the hardware and software foundation for others to operate on. This transformation signals a major shift in how capitalist firms operate and how they interact with the rest of the economy: the emergence of ‘platform capitalism’.

This book critically examines these new business forms, tracing their genesis from the long downturn of the 1970s to the boom and bust of the 1990s and the aftershocks of the 2008 crisis. It shows how the fundamental foundations of the economy are rapidly being carved up among a small number of monopolistic platforms, and how the platform introduces new tendencies within capitalism that pose significant challenges to any vision of a post-capitalist future. This book will be essential reading for anyone who wants to understand how the most powerful tech companies of our time are transforming the global economy.""

also this

--Marxism and Critical theory tags are tentative as the author belongs to *speculative realism* school, which allegedly moves beyond anti-realist tendencies of the past
GAFA  capitalism  market_failures  monopoly  critique  book  critical_theory  marxism  ? 
january 2018 by rvenkat
Critical dynamics in population vaccinating behavior
Vaccine refusal can lead to renewed outbreaks of previously eliminated diseases and even delay global eradication. Vaccinating decisions exemplify a complex, coupled system where vaccinating behavior and disease dynamics influence one another. Such systems often exhibit critical phenomena—special dynamics close to a tipping point leading to a new dynamical regime. For instance, critical slowing down (declining rate of recovery from small perturbations) may emerge as a tipping point is approached. Here, we collected and geocoded tweets about measles–mumps–rubella vaccine and classified their sentiment using machine-learning algorithms. We also extracted data on measles-related Google searches. We find critical slowing down in the data at the level of California and the United States in the years before and after the 2014–2015 Disneyland, California measles outbreak. Critical slowing down starts growing appreciably several years before the Disneyland outbreak as vaccine uptake declines and the population approaches the tipping point. However, due to the adaptive nature of coupled behavior–disease systems, the population responds to the outbreak by moving away from the tipping point, causing “critical speeding up” whereby resilience to perturbations increases. A mathematical model of measles transmission and vaccine sentiment predicts the same qualitative patterns in the neighborhood of a tipping point to greatly reduced vaccine uptake and large epidemics. These results support the hypothesis that population vaccinating behavior near the disease elimination threshold is a critical phenomenon. Developing new analytical tools to detect these patterns in digital social data might help us identify populations at heightened risk of widespread vaccine refusal.
epidemiology  sentiment_analysis  contagion  networked_life  ?  dynamics  phase_transition 
december 2017 by rvenkat
Policy Preferences and Policy Change: Dynamic Responsiveness in the American States, 1936–2014 | American Political Science Review | Cambridge Core
Using eight decades of data, we examine the magnitude, mechanisms, and moderators of dynamic responsiveness in the American states. We show that on both economic and (especially) social issues, the liberalism of state publics predicts future change in state policy liberalism. Dynamic responsiveness is gradual, however; large policy shifts are the result of the cumulation of incremental responsiveness over many years. Partisan control of government appears to mediate only a fraction of responsiveness, suggesting that, contrary to conventional wisdom, responsiveness occurs in large part through the adaptation of incumbent officials. Dynamic responsiveness has increased over time but does not seem to be influenced by institutions such as direct democracy or campaign finance regulations. We conclude that our findings, though in some respects normatively ambiguous, on the whole paint a reassuring portrait of statehouse democracy.
democracy  public_opinion  public_policy  political_science  causal_inference  ?  via:nyhan 
november 2017 by rvenkat
[1711.05701] Social Complex Contagion in Music Listenership: A Natural Experiment with 1.3 Million Participants
Can live music events generate complex contagion in music streaming? This paper finds evidence in the affirmative, but only for the most popular artists. We generate a novel dataset from Last.fm, a music tracking website, to analyse the listenership history of 1.3 million users over a two-month time horizon. We use daily play counts along with event attendance data to run a regression discontinuity analysis in order to show the causal impact of concert attendance on music listenership among attendees and their friends network. First, we show that attending a music artist's live concert increases that artist's listenership among the attendees of the concert by approximately 1 song per day per attendee (p-value<0.001). Moreover, we show that this effect is contagious and can spread to users who did not attend the event. However, the extent of contagion depends on the type of artist. We only observe contagious increases in listenership for well-established, popular artists (.06 more daily plays per friend of an attendee [p<0.001]), while the effect is absent for emerging stars. We also show that the contagion effect size increases monotonically with the number of friends who have attended the live event.
contagion  homophily  ?  causal_inference  natural_experiment  epidemics  networks  teaching  via:strogatz 
november 2017 by rvenkat
Oscillators that sync and swarm | Nature Communications
Synchronization occurs in many natural and technological systems, from cardiac pacemaker cells to coupled lasers. In the synchronized state, the individual cells or lasers coordinate the timing of their oscillations, but they do not move through space. A complementary form of self-organization occurs among swarming insects, flocking birds, or schooling fish; now the individuals move through space, but without conspicuously altering their internal states. Here we explore systems in which both synchronization and swarming occur together. Specifically, we consider oscillators whose phase dynamics and spatial dynamics are coupled. We call them swarmalators, to highlight their dual character. A case study of a generalized Kuramoto model predicts five collective states as possible long-term modes of organization. These states may be observable in groups of sperm, Japanese tree frogs, colloidal suspensions of magnetic particles, and other biological and physical systems in which self-assembly and synchronization interact.


active_matter  synchronization  self_organization  collective_dynamics  collective_animal_behavior  ?  steven.strogatz 
november 2017 by rvenkat
The Oldest Living Things in the World, Sussman, Zimmer, Obrist
The Oldest Living Things in the World is an epic journey through time and space. Over the past decade, artist Rachel Sussman has researched, worked with biologists, and traveled the world to photograph continuously living organisms that are 2,000 years old and older. Spanning from Antarctica to Greenland, the Mojave Desert to the Australian Outback, the result is a stunning and unique visual collection of ancient organisms unlike anything that has been created in the arts or sciences before, insightfully and accessibly narrated by Sussman along the way.

Her work is both timeless and timely, and spans disciplines, continents, and millennia. It is underscored by an innate environmentalism and driven by Sussman’s relentless curiosity. She begins at “year zero,” and looks back from there, photographing the past in the present. These ancient individuals live on every continent and range from Greenlandic lichens that grow only one centimeter a century, to unique desert shrubs in Africa and South America, a predatory fungus in Oregon, Caribbean brain coral, to an 80,000-year-old colony of aspen in Utah. Sussman journeyed to Antarctica to photograph 5,500-year-old moss; Australia for stromatolites, primeval organisms tied to the oxygenation of the planet and the beginnings of life on Earth; and to Tasmania to capture a 43,600-year-old self-propagating shrub that’s the last individual of its kind. Her portraits reveal the living history of our planet—and what we stand to lose in the future. These ancient survivors have weathered millennia in some of the world’s most extreme environments, yet climate change and human encroachment have put many of them in danger. Two of her subjects have already met with untimely deaths by human hands.

Alongside the photographs, Sussman relays fascinating – and sometimes harrowing – tales of her global adventures tracking down her subjects and shares insights from the scientists who research them. The oldest living things in the world are a record and celebration of the past, a call to action in the present, and a barometer of our future.
book  biology  via:  ? 
november 2017 by rvenkat
[1708.03015] An Empirical Study on Team Formation in Online Games
Online games provide a rich recording of interactions that can contribute to our understanding of human behavior. One potential lesson is to understand what motivates people to choose their teammates and how their choices leadto performance. We examine several hypotheses about team formation using a large, longitudinal dataset from a team-based online gaming environment. Specifically, we test how positive familiarity, homophily, and competence determine team formationin Battlefield 4, a popular team-based game in which players choose one of two competing teams to play on. Our dataset covers over two months of in-game interactions between over 380,000 players. We show that familiarity is an important factorin team formation, while homophily is not. Competence affects team formation in more nuanced ways: players with similarly high competence team-up repeatedly, but large variations in competence discourage repeated interactions.

-- the networks tag apply most because team formation dynamics may explain network formation. The paper never directly discusses network formation.
social_networks  observational_studies  homophily  dynamics  networks  teaching  collective_cognition  ? 
november 2017 by rvenkat
Someone ‘Accidentally’ Locked Away $300M Worth of Other People's Ethereum Funds - Motherboard
-- what people refuse to understand is that these decentralized systems still have material constraints and are prone to human errors. A promise of a democratic institution without _elites_ or _authority_ should have a way of guaranteeing reliability and immunity from human errors.
blockchain  cryptocurrency  automation  institutions  algorithms  technology  democracy  ?  motherboard 
november 2017 by rvenkat
Feigenbaum: How High-Income Neighborhoods Receive More Service from Municipal Government: Evidence from City Administrative Data
Municipal governments oversee many of the most important political matters of daily life in the U.S., yet our understanding of municipal politics remains limited. We combine a large dataset of requests for local government services—such as snow plowing, traffic signal repairs, pothole repairs, and graffiti cleanup—in Boston, Massachusetts, 2011–2015, with fine-grained census data on localized incomes and income inequality. Employing a within-neighborhood design, we establish that, other things equal, higher-income census tracts make more requests for government services. Using data from open-ended text responses submitted by the city, we then connect these requests to the provision of services, showing how the underlying capacity of local communities for communicating requests—i.e., for participating in the process of local government—helps drive inequality in the receipt of services themselves. These results highlight how inequality in economic resources connects to inequality in the non-electoral components of participation in local government.

big_data  econometrics  administrative_state  governance  wealth  inequality  technology  cities  geography  spatial_statistics  political_economy  public_goods  public_administration  ? 
october 2017 by rvenkat
Ape parasite origins of human malaria virulence genes | Nature Communications
Antigens encoded by the var gene family are major virulence factors of the human malaria parasite Plasmodium falciparum, exhibiting enormous intra- and interstrain diversity. Here we use network analysis to show that var architecture and mosaicism are conserved at multiple levels across the Laverania subgenus, based on var-like sequences from eight single-species and three multi-species Plasmodium infections of wild-living or sanctuary African apes. Using select whole-genome amplification, we also find evidence of multi-domain var structure and synteny in Plasmodium gaboni, one of the ape Laverania species most distantly related to P. falciparum, as well as a new class of Duffy-binding-like domains. These findings indicate that the modular genetic architecture and sequence diversity underlying var-mediated host-parasite interactions evolved before the radiation of the Laverania subgenus, long before the emergence of P. falciparum.

Larremore, Clauset paper

Also see
Plasmodium falciparum population genetic complexity influences expression dynamics and immune recognition among highly related genotypic clusters" (under review)

class discussion or online discussion idea?
genetics  networks  biology  teaching  ? 
october 2017 by rvenkat
Rumor Has It: The Adoption of Unverified Information in Conflict Zones | International Studies Quarterly | Oxford Academic
Rumors run rife in areas affected by political instability and conflict. Their adoption plays a key role in igniting many forms of violence, including riots, ethnic conflict, genocide, and war. While unverified at the time of transmission, some rumors are widely treated as truth, while others are dismissed as implausible or false. What factors lead individuals to embrace rumors and other forms of unverified information? This article presents a new theoretical framework for understanding individual receptivity to rumors and tests it using original survey data gathered in insurgency-affected areas of Thailand and the Philippines. We find wide variation in rumor adoption, and argue that three factors drive individuals to embrace rumors: worldview, threat perception, and prior exposure. Contrary to conventional wisdom, we find no evidence that commonly cited factors—including education, income, age, and gender—determine individual receptivity to rumors. We also explore the implications of belief in rumors on conflict dynamics. We find that greater receptivity to rumors correlates with the belief that ongoing conflict is intractable. This suggests that rumors can not only help spark political violence, but also impede its resolution. Our findings shed light on the complex interaction between worldview and unverified information in shaping popular beliefs—and through them, political contention and competition—in conflict areas and beyond.
public_opinion  common_knowledge  ?  conspiracy_theories  cultural_cognition  dmce  teaching  via:nyhan  models_of_behavior 
october 2017 by rvenkat
Now out of Never: The Element of Surprise in the East European Revolution of 1989 | World Politics | Cambridge Core
Like many major revolutions in history, the East European Revolution of 1989 caught its leaders, participants, victims, and observers by surprise. This paper offers an explanation whose crucial feature is a distinction between private and public preferences. By suppressing their antipathies to the political status quo, the East Europeans misled everyone, including themselves, as to the possibility of a successful uprising. In effect, they conferred on their privately despised governments an aura of invincibility. Under the circumstances, public opposition was poised to grow explosively if ever enough people lost their fear of exposing their private preferences. The currently popular theories of revolution do not make clear why uprisings easily explained in retrospect may not have been anticipated. The theory developed here fills this void. Among its predictions is that political revolutions will inevitably continue to catch the world by surprise.
european_politics  revolutions  20th_century  social_behavior  contagion  homophily  ?  social_psychology  institutions  norms  collective_dynamics  judgment_decision-making  dmce  teaching  timur.kuran 
october 2017 by rvenkat
Private Truths, Public Lies — Timur Kuran | Harvard University Press
Preference falsification, according to the economist Timur Kuran, is the act of misrepresenting one’s wants under perceived social pressures. It happens frequently in everyday life, such as when we tell the host of a dinner party that we are enjoying the food when we actually find it bland. In Private Truths, Public Lies, Kuran argues convincingly that the phenomenon not only is ubiquitous but has huge social and political consequences. Drawing on diverse intellectual traditions, including those rooted in economics, psychology, sociology, and political science, Kuran provides a unified theory of how preference falsification shapes collective decisions, orients structural change, sustains social stability, distorts human knowledge, and conceals political possibilities.

A common effect of preference falsification is the preservation of widely disliked structures. Another is the conferment of an aura of stability on structures vulnerable to sudden collapse. When the support of a policy, tradition, or regime is largely contrived, a minor event may activate a bandwagon that generates massive yet unanticipated change.

In distorting public opinion, preference falsification also corrupts public discourse and, hence, human knowledge. So structures held in place by preference falsification may, if the condition lasts long enough, achieve increasingly genuine acceptance. The book demonstrates how human knowledge and social structures co-evolve in complex and imperfectly predictable ways, without any guarantee of social efficiency.

Private Truths, Public Lies uses its theoretical argument to illuminate an array of puzzling social phenomena. They include the unexpected fall of communism, the paucity, until recently, of open opposition to affirmative action in the United States, and the durability of the beliefs that have sustained India’s caste system
book  social_behavior  contagion  homophily  ?  social_psychology  institutions  norms  collective_dynamics  judgment_decision-making  dmce  teaching  timur.kuran 
october 2017 by rvenkat
Improving Crop Estimates by Integrating Multiple Data Sources | The National Academies Press
The National Agricultural Statistics Service (NASS) is the primary statistical data collection agency within the U.S. Department of Agriculture (USDA). NASS conducts hundreds of surveys each year and prepares reports covering virtually every aspect of U.S. agriculture. Among the small-area estimates produced by NASS are county-level estimates for crops (planted acres, harvested acres, production, and yield by commodity) and for cash rental rates for irrigated cropland, nonirrigated cropland, and permanent pastureland. Key users of these county-level estimates include USDA’s Farm Services Agency (FSA) and Risk Management Agency (RMA), which use the estimates as part of their processes for distributing farm subsidies and providing farm insurance, respectively.

Improving Crop Estimates by Integrating Multiple Data Sources assesses county-level crop and cash rents estimates, and offers recommendations on methods for integrating data sources to provide more precise county-level estimates of acreage and yield for major crops and of cash rents by land use. This report considers technical issues involved in using the available data sources, such as methods for integrating the data, the assumptions underpinning the use of each source, the robustness of the resulting estimates, and the properties of desirable estimates of uncertainty.
nap  report  spatial_statistics  data_fusion  statistics  machine_learning  ?  for_friends 
october 2017 by rvenkat
Do Anti-Immigrant Laws Shape Public Sentiment? A Study of Arizona’s SB 1070 Using Twitter Data: American Journal of Sociology: Vol 123, No 2
Scholars have debated whether laws can influence public opinion, but evidence of these “feedback” effects is scant. This article examines the effect of Arizona’s 2010 high-profile anti-immigrant law, SB 1070, on both public attitudes and behaviors toward immigrants. Using sentiment analysis and a difference-in-difference approach to analyze more than 250,000 tweets, the author finds that SB 1070 had a negative impact on the average sentiment of tweets regarding immigrants, Mexicans, and Hispanics, but not on those about Asians or blacks. However, these changes in public discourse were not caused by shifting attitudes toward immigrants but by the mobilization of anti-immigrant users and by motivating new users to begin tweeting. While some scholars propose that punitive laws can shape people’s attitudes toward targeted groups, this study shows that policies are more likely to influence behaviors. Rather than placating the electorate, anti-immigrant laws may stir the pot further, mobilizing individuals already critical of immigrants.
law  public_opinion  mediation_analysis  causal_inference  ?  media_studies  twitter  political_psychology  us_politics  via:nyhan 
october 2017 by rvenkat
Access to Health Care and Criminal Behavior: Short-Run Evidence from the ACA Medicaid Expansions by Jacob Vogler :: SSRN
I investigate the causal relationship between access to health care and criminal behavior following state decisions to expand Medicaid coverage after the Affordable Care Act. Many of the newly eligible individuals for Medicaid-provided health insurance are adults at high risk for crime. I leverage variation in both insurance eligibility generated by state decisions to expand Medicaid and county-level treatment intensity measured by changes in insurance rates. My findings indicate that the Medicaid expansions have resulted in significant decreases in annual rates of reported crime, including both property and violent crime, by between 3 to 5 percent per 100,000 people. A within-state heterogeneity analysis suggests that crime impacts are more pronounced in counties that experienced larger gains in insurance rates among individuals newly eligible for Medicaid coverage. The estimated decrease in reported crime amounts to an annual cost savings of nearly $400 million.
ACA  health  crime  poverty  causal_inference  ?  united_states_of_america  i_remain_skeptical 
october 2017 by rvenkat
The Space between Us by Ryan D. Enos
The Space Between Us brings the connection between geography, psychology, and politics to life. By going into the neighborhoods of real cities, Enos shows how our perceptions of racial, ethnic, and religious groups are intuitively shaped by where these groups live and interact daily. Through the lens of numerous examples across the globe and drawing on a compelling combination of research techniques including field and laboratory experiments, big data analysis, and small-scale interactions, this timely book provides a new understanding of how geography shapes politics and how members of groups think about each other. Enos' analysis is punctuated with personal accounts from the field. His rigorous research unfolds in accessible writing that will appeal to specialists and non-specialists alike, illuminating the profound effects of social geography on how we relate to, think about, and politically interact across groups in the fabric of our daily lives.
book  geography  political_psychology  political_science  spatial_statistics  political_sociology  big_data  experiments  homophily  social_networks  networks  teaching  ? 
october 2017 by rvenkat
One Long Night
A groundbreaking, haunting, and profoundly moving history of modernity’s greatest tragedy: concentration camps

For over 100 years, at least one concentration camp has existed somewhere on Earth. First used as battlefield strategy, camps have evolved with each passing decade, in the scope of their effects and the savage practicality with which governments have employed them. Even in the twenty-first century, as we continue to reckon with the magnitude and horror of the Holocaust, history tells us we have broken our own solemn promise of “never again.”

In this harrowing work based on archival records and interviews during travel to four continents, Andrea Pitzer reveals for the first time the chronological and geopolitical history of concentration camps. Beginning with 1890s Cuba, she pinpoints concentration camps around the world and across decades. From the Philippines and Southern Africa in the early twentieth century to the Soviet Gulag and detention camps in China and North Korea during the Cold War, camp systems have been used as tools for civilian relocation and political repression. Often justified as a measure to protect a nation, or even the interned groups themselves, camps have instead served as brutal and dehumanizing sites that have claimed the lives of millions.

Drawing from exclusive testimony, landmark historical scholarship, and stunning research, Andrea Pitzer unearths the roots of this appalling phenomenon, exploring and exposing the staggering toll of the camps: our greatest atrocities, the extraordinary survivors, and even the intimate, quiet moments that have also been part of camp life during the past century.
book  history  modernity  concentration_camps  ethnic_cleansing  ?  world_history  19th_century  20th_century  21st_century 
september 2017 by rvenkat
Meta-analysis of field experiments shows no change in racial discrimination in hiring over time
Many scholars have argued that discrimination in American society has decreased over time, while others point to persisting race and ethnic gaps and subtle forms of prejudice. The question has remained unsettled due to the indirect methods often used to assess levels of discrimination. We assess trends in hiring discrimination against African Americans and Latinos over time by analyzing callback rates from all available field experiments of hiring, capitalizing on the direct measure of discrimination and strong causal validity of these studies. We find no change in the levels of discrimination against African Americans since 1989, although we do find some indication of declining discrimination against Latinos. The results document a striking persistence of racial discrimination in US labor markets.

-- a potential HW, linking this with Granovetter's work?
race  discrimination  economic_sociology  labor  microeconomics  meta-analysis  united_states_of_america  networks  teaching  ? 
september 2017 by rvenkat
Significant social change often comes from the unleashing of hidden preferences; it also comes from the construction of novel preferences. Under the pressure of social norms, people sometimes falsify their preferences. They do not feel free to say or do as they wish. Once norms are weakened or revised, through private efforts or law, it becomes possible to discover preexisting preferences. Because those preferences existed but were concealed, large-scale movements are both possible and exceedingly difficult to predict; they are often startling. But revisions of norms can also construct rather than uncover preferences. Once norms are altered, again through private efforts or law, people come to hold preferences that they did not hold before. Nothing has been unleashed. These points bear on the rise and fall (and rise again, and fall again) of discrimination on the basis of sex and race (and also religion and ethnicity). They also help illuminate the dynamics of social cascades and the effects of social norms on diverse practices and developments, including smoking, drinking, police brutality, protest activity, veganism, drug use, crime, white nationalism, “ethnification,” considerateness, and the public expression of religious beliefs.
social_behavior  contagion  homophily  ?  social_psychology  institutions  norms  collective_dynamics  cass.sunstein  judgment_decision-making  dmce  teaching 
august 2017 by rvenkat
Rationally Inattentive Behavior: Characterizing and Generalizing Shannon Entropy
We provide a full behavioral characterization of the standard Shannon model of rational inattention. The key axiom is "Invariance under Compression", which identifies this model as capturing an ideal form of attention-constrained choice. We introduce tractable generalizations that allow for many of the known behavioral violations from this ideal, including asymmetries and complementarities in learning, context effects, and low responsiveness to incentives. We provide an even more general method of recovering attention costs from behavioral data. The data set in which we characterize all behavioral patterns is "state dependent" stochastic choice data.
economics  information_theory  heuristics  judgment_decision-making  dmce  teaching  ?  nber 
august 2017 by rvenkat
Religious networks roman empire spread new ideas | Ancient history | Cambridge University Press
The first three centuries AD saw the spread of new religious ideas through the Roman Empire, crossing a vast and diverse geographical, social and cultural space. In this innovative study, Anna Collar explores both how this happened and why. Drawing on research in the sociology and anthropology of religion, physics and computer science, Collar explores the relationship between social networks and religious transmission to explore why some religious movements succeed, while others, seemingly equally successful at a certain time, ultimately fail. Using extensive epigraphic data, Collar provides new interpretations of the diffusion of ideas across the social networks of the Jewish Diaspora and the cults of Jupiter Dolichenus and Theos Hypsistos, and in turn offers important reappraisals of the spread of religious innovations in the Roman Empire. This study will be a valuable resource for students and scholars of ancient history, archaeology, ancient religion and network theory.
book  archaelogy  history_of_ideas  epidemiology_of_representations  religion  social_networks  ?  teaching  networks  via:sunstein 
august 2017 by rvenkat
Political Theory of the Firm
The revenues of large companies often rival those of national governments, and some companies have annual revenues higher than many national governments. Among the largest corporations in 2015, some had private security forces that rivaled the best secret services, public relations offices that dwarfed a US presidential campaign headquarters, more lawyers than the US Justice Department, and enough money to capture (through campaign donations, lobbying, and even explicit bribes) a majority of the elected representatives. The only powers these large corporations missed were the power to wage war and the legal power of detaining people, although their political influence was sufficiently large that many would argue that, at least in certain settings, large corporations can exercise those powers by proxy. Yet in economics, the commonly prevailing view of the firm ignores all these elements of politics and power. We must recognize that large firms have considerable power to influence the rules of the game. I call attention to the risk of a "Medici vicious circle," in which economic and political power reinforce each other. The possibility and extent of a "Medici vicious circle" depends upon several nonmarket factors. I discuss how they should be incorporated in a broader "Political Theory" of the firm.
political_economy  review  microeconomics  ?  via:noahpinion 
august 2017 by rvenkat
The Belief in a Favorable FuturePsychological Science - Todd Rogers, Don A. Moore, Michael I. Norton, 2017
People believe that future others’ preferences and beliefs will change to align with their own. People holding a particular view (e.g., support of President Trump) are more likely to believe that future others will share their view than to believe that future others will have an opposing view (e.g., opposition to President Trump). Six studies demonstrated this belief in a favorable future (BFF) for political views, scientific beliefs, and entertainment and product preferences. BFF is greater in magnitude than the tendency to believe that current others share one’s views (false-consensus effect), arises across cultures, is distinct from general optimism, is strongest when people perceive their views as being objective rather than subjective, and can affect (but is distinct from) beliefs about favorable future policy changes. A lab experiment involving monetary bets on the future popularity of politicians and a field experiment involving political donations (N = 660,542) demonstrated that BFF can influence people’s behavior today.
prediction  judgment_decision-making  heuristics  the_civilizing_process  critique  ?  teaching  moral_values  human_progress 
august 2017 by rvenkat
Contagion During the Initial Banking Panic of the Great Depression
The initial banking crisis of the Great Depression has been the subject of debate. Some scholars believe a contagious panic spread among financial institutions. Others argue that suspensions surged because fundamentals, such as losses on loans, drove banks out of business. This paper nests those hypotheses in a single econometric framework, a Bayesian hazard rate model with spatial and network effects. New data on correspondent networks and bank locations enables us to determine which hypothesis fits the data best. The best fitting models are ones incorporating network and geographic effects. The results are consistent with the description of events by depression-era bankers, regulators, and newspapers. Contagion - both interbank and spatial - propelled a panic which healthy banks survived but which forced illiquid and insolvent banks out of operations.
econometrics  finance  networks  teaching  ?  nber 
august 2017 by rvenkat
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