A Random World Is a Fair World
A preference for fairness or equity in the distribution of resources influences many human decisions. The origin of this preference is a topic that has consumed philosophers, social scientists, and biologists for centuries. However, although we feel a sense of fairness deeply and intuitively, it has so far been difficult to explain from first principles how such a feeling might have evolved. How could natural selection allow for the survival of "fair" individuals who sometimes give things away to equalize resources when they must compete with self-interested individuals who keep everything for themselves? In PNAS, Rand et al. provide a unique and compelling solution to this puzzle: it's all because of dumb luck.
A 61-Million-Person Experiment in Social Influence and Political Mobilization
Human behaviour is theorized to spread via face-to-face social networks, but it is difficult to identify social influence effects in observational studies and it is unknown whether online social networks operate in the same way. Here, we report results from a randomized controlled trial of political mobilization messages delivered to 61 million Facebook users during the 2010 U.S. Congressional elections. The results show that the messages directly influenced political self-expression, information seeking, and real world voting behaviour of millions of people. Furthermore, the messages not only influenced the users who received them, but the users' friends and friends of friends as well. The effect of social transmission on real world voting was larger than the direct effect of the messages themselves, and nearly all the transmission occurred between "close friends" who were more likely to have a face-to-face relationship. These results suggest that strong ties are instrumental for spreading both online and real world behaviour in human social networks.
Biologist E. O. Wilson's brilliant new volume, The Social Conquest of Earth, could more aptly be entitled 'Biology's Conquest of Science'. Drawing on his deep understanding of entomology and his extraordinarily broad knowledge of the natural and social sciences, Wilson makes a strong case for the synthesis of knowledge across disciplines. Understanding the biological origin of what makes us human can help us to build better theories of social and psychological interaction; in turn, understanding how other social species have evolved may help us to better understand the origin of our own. But the main reason that Wilson's book is successful is that he also brings into biology the best of what social science has to offer. He draws on careful work in linguistics, psychology, economics, religious studies and the arts to elaborate on differences between humans and other species. This give and take, this flow of ideas across disciplines, allows him to study an intriguing set of questions. Why did ants and humans both become social? What is it about being social that helped both species to achieve evolutionary success? And if it worked so well, why aren't all other species like us?
The Neural Basis of Egalitarian Behavior
Individuals are willing to sacrifice their own resources to promote equality in groups. These costly choices promote equality and are associated with behavior that supports cooperation in humans, but little is known about the brain processes involved. We use functional MRI to study egalitarian preferences based on behavior observed in the "random income game." In this game, subjects decide whether to pay a cost to alter group members' randomly allocated incomes. We specifically examine whether egalitarian behavior is associated with neural activity in the ventromedial prefrontal cortex and the insular cortex, two regions that have been shown to be related to social preferences. Consistent with previous studies, we find significant activation in both regions; however, only the insular cortex activations are significantly associated with measures of revealed and expressed egalitarian preferences elicited outside the scanner. These results are consistent with the notion that brain mechanisms involved in experiencing the emotional states of others underlie egalitarian behavior in humans.
Social Networks and Cooperation in Hunter-Gatherers
Social networks show striking structural regularities, and both theory and evidence suggest that networks may have facilitated the development of large-scale cooperation in humans. Here, we characterize the social networks of the Hadza, a population of hunter-gatherers in Tanzania. We show that Hadza networks have important properties also seen in modernized social networks, including a skewed degree distribution, degree assortativity, transitivity, reciprocity, geographic decay and homophily. We demonstrate that Hadza camps exhibit high between-group and low within-group variation in public goods game donations. Network ties are also more likely between people who give the same amount, and the similarity in cooperative behaviour extends up to two degrees of separation. Social distance appears to be as important as genetic relatedness and physical proximity in explaining assortativity in cooperation. Our results suggest that certain elements of social network structure may have been present at an early point in human history. Also, early humans may have formed ties with both kin and non-kin, based in part on their tendency to cooperate. Social networks may thus have contributed to the emergence of cooperation.
The Evolution of Overconfidence
Confidence is an essential ingredient of success in a wide range of domains ranging from job performance and mental health to sports, business and combat. Some authors have suggested that not just confidence but overconfidence -- believing you are better than you are in reality -- is advantageous because it serves to increase ambition, morale, resolve, persistence or the credibility of bluffing, generating a self-fulfilling prophecy in which exaggerated confidence actually increases the probability of success. However, overconfidence also leads to faulty assessments, unrealistic expectations and hazardous decisions, so it remains a puzzle how such a false belief could evolve or remain stable in a population of competing strategies that include accurate, unbiased beliefs. Here we present an evolutionary model showing that, counterintuitively, overconfidence maximizes individual fitness and populations tend to become overconfident, as long as benefits from contested resources are sufficiently large compared with the cost of competition. In contrast, unbiased strategies are only stable under limited conditions. The fact that overconfident populations are evolutionarily stable in a wide range of environments may help to explain why overconfidence remains prevalent today, even if it contributes to hubris, market bubbles, financial collapses, policy failures, disasters and costly wars.
Correlated Genotypes in Friendship Networks
It is well known that humans tend to associate with other humans who have similar characteristics, but it is unclear whether this tendency has consequences for the distribution of genotypes in a population. Although geneticists have shown that populations tend to stratify genetically, this process results from geographic sorting or assortative mating, and it is unknown whether genotypes may be correlated as a consequence of non-reproductive associations or other processes. Here, we study six available genotypes from the National Longitudinal Study of Adolescent Health to test for genetic similarity between friends. Maps of the friendship networks show clustering of genotypes, and, after we apply strict controls for population stratification, the results show that one genotype is positively correlated (homophily) and one genotype is negatively correlated (heterophily). A replication study on an independent sample from the Framingham Heart Study verifies that DRD2 exhibits significant homophily and that CYP2A6 exhibits significant heterophily. These novel results show that homophily and heterophily obtain on a genetic (indeed, an allelic) level, which has implications for the study of population genetics and social behavior. In particular, the results suggest that association tests should include friends' genes and that theories of evolution should take into account the fact that humans might, in some sense, be "metagenomic" with respect to the humans around them.
Cooperative Behavior Cascades in Human Social Networks
Theoretical models suggest that social networks influence the evolution of cooperation, but to date there have been few experimental studies. Observational data suggest that a wide variety of behaviors may spread in human social networks, but subjects in such studies can choose to befriend people with similar behaviors, posing difficulty for causal inference. Here, we exploit a seminal set of laboratory experiments that originally showed that voluntary costly punishment can help sustain cooperation. In these experiments, subjects were randomly assigned to a sequence of different groups in order to play a series of single-shot public goods games with strangers; this feature allowed us to draw networks of interactions to explore how cooperative and uncooperative behavior spreads from person to person to person. We show that, in both an ordinary public goods game and in a public goods game with punishment, focal individuals are influenced by fellow group members' contribution behavior in future interactions with other individuals who were not a party to the initial interaction. Furthermore, this influence persists for multiple periods and spreads up to three degrees of separation (from person to person to person to person). The results suggest that each additional contribution a subject makes to the public good in the first period is tripled over the course of the experiment by other subjects who are directly or indirectly influenced to contribute more as a consequence. These are the first results to show experimentally that cooperative behavior cascades in human social networks.
Model of Genetic Variation in Human Social Networks
Social networks influence the evolution of cooperation and they exhibit strikingly systematic patterns across a wide range of human contexts. Both of these facts suggest that variation in the topological attributes of human social networks might have a genetic basis. While genetic variation accounts for a significant portion of the variation in many complex social behaviors, the heritability of egocentric social network attributes is unknown. Here we show that three of these attributes (in-degree, transitivity, and centrality) are heritable. We then develop a 'mirror network' method to test extant network models and show that none accounts for observed genetic variation in human social networks. We propose an alternative 'attract and introduce' model that generates significant heritability as well as other important network features, and we show that this model with two simple forms of heterogeneity is well suited to the modeling of real social networks in human! s. These results suggest that natural selection may have played a role in the evolution of social networks. They also suggest that modeling intrinsic variation in network attributes may be important for understanding the way genes affect human behaviors and the way these behaviors spread from person to person.
Computational Social Science
We live life in the network. We check our e-mails regularly, make mobile phone calls from almost any location, swipe transit cards to use public transportation, and make purchases with credit cards. Our movements in public places may be captured by video cameras, and our medical records stored as digital files. We may post blog entries accessible to anyone, or maintain friendships through online social networks. Each of these transactions leaves digital traces that can be compiled into comprehensive pictures of both individuals and group behavior, with the potential to transform our understanding of our lives, organizations, and societies.
Biology, Politics, and the Emerging Science of Human Nature
In the past fifty years, biologists have learned a tremendous amount about human brain function and its genetic basis. At the same time political scientists have been intensively studying the effect of the social and institutional environment on mass political attitudes and behaviors. However, these separate fields of inquiry are subject to inherent limitations that may only be resolved through collaboration across disciplines. Here we describe recent advances in the emerging fields of genopolitics and neuropolitics and argue that biologists and political scientists must work together to advance a new science of human nature.
Heritability of Cooperative Behavior in the Trust Game
Although laboratory experiments document cooperative behavior in humans, little is known about the extent to which individual differences in cooperativeness result from genetic and environmental variation. In this article we report the results of two independently conceived and executed studies of monozygotic and dizygotic twins, one in Sweden, and one in the United States. The results from these studies suggest that humans are endowed with genetic variation that influences the decision to invest--and to reciprocate investment--in the classic trust game. Based on these findings, we urge social scientists to take seriously the idea that differences in peer and parental socialization are not the only forces that influence variation in cooperative behavior.
Egalitarian Motives in Humans
Participants in laboratory games are often willing to alter others' incomes at a cost to themselves and this behaviour has the effect of promoting cooperation. What motivates this action is unclear: punishment and reward aimed at promoting cooperation cannot be distinguished from attempts to produce equality. To understand costly taking and costly giving, we create an experimental game that isolates egalitarian motives. The results show that subjects reduce and augment others' incomes, at a personal cost, even when there is no cooperative behaviour to be reinforced. Furthermore, the size and frequency of income alterations are strongly influenced by inequality. Emotions towards top earners become increasingly negative as inequality increases, and those who express these emotions spend more to reduce above-average earners' incomes and to increase below-average earners' incomes. The results suggest that egalitarian motives affect income altering behaviours, and may thus be an important factor underlying the evolution of strong reciprocity and, hence, cooperation in humans.
Mandates, Parties, and Voters: How Elections Shape the Future
Most research on two-party elections has considered the outcome as a single, dichotomous event: either one or the other party wins. In this book, the authors investigate not just who wins, but by how much, and they marshal compelling evidence that mandates--in the form of margin of victory--matter. Using theoretical models, computer simulation, carefully designed experiments, and empirical data, the authors show that after an election the policy positions of both parties move in the direction preferred by the winning party--and they move even more if the victory is large.
Second Order Free-Riding Problem Solved?
Panchanathan and Boyd describe a model of indirect reciprocity in which mutual aid among cooperators can promote large-scale human cooperation without succumbing to a second-order free-riding problem (whereby individuals receive but do not give aid). However, the model does not include second-order free riders as one of the possible behavioural types. Here I present a simplified version of their model to demonstrate how cooperation unravels if second-round defectors enter the population, and this shows that the free-riding problem remains unsolved.
Altruistic Punishment and the Origin of Cooperation
How did human cooperation evolve? Recent evidence shows that many people are willing to engage in altruistic punishment, voluntarily paying a cost to punish noncooperators. Although this behavior helps to explain how cooperation can persist, it creates an important puzzle. If altruistic punishment provides benefits to nonpunishers and is costly to punishers, then how could it evolve? Drawing on recent insights from voluntary public goods games, I present a simple evolutionary model in which altruistic punishers can enter and will always come to dominate a population of contributors, defectors, and nonparticipants. The model suggests that the cycle of strategies in voluntary public goods games does not persist in the presence of punishment strategies. It also suggests that punishment can only enforce payoff-improving strategies, contrary to a widely cited "folk theorem" result that suggests that punishment can allow the evolution of any strategy.
Egalitarian Motive and Altruistic Punishment
Altruistic punishment is a behaviour in which individuals punish others at a cost to themselves in order to provide a public good. Fehr and Gachter present experimental evidence suggesting that negative emotions toward non-cooperators motivate punishment which, in turn, facilitates high levels of cooperation in humans. Using Fehr and Gachter's original data, we provide an alternative analysis of the experiment that suggests egalitarian motives are more important than motives to punish non-cooperative behaviour--a finding consistent with evidence that humans may have an evolutionary incentive to punish the highest earners in order to promote equality, not cooperation.
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Social Contagion Theory: Examining Dynamic Social Networks and Human Behavior
Here, we review the research we have done on social contagion. We describe the methods we have employed (and the assumptions they have entailed) in order to examine several datasets with complementary strengths and weaknesses, including the Framingham Heart Study, the National Longitudinal Study of Adolescent Health, and other observational and experimental datasets. We describe the regularities that led us to propose that human social networks may exhibit a "three degrees of influence" property, and we review statistical approaches we have used to characterize inter-personal influence with respect to behaviors like obesity and affective states like happiness. We do not claim that this work is the final word, but we do believe that it provides some novel, informative, and stimulating evidence regarding social contagion in longitudinally followed networks. Along with other scholars, we are working to develop new methods for identifying causal effects using social network data, and we believe that this area is ripe for statistical development as current methods have known and often unavoidable limitations.
Social Network Sensors for Early Detection of Contagious Outbreaks
Current methods for the detection of contagious outbreaks give contemporaneous information about the course of an epidemic at best. It is known that individuals near the center of a social network are likely to be infected sooner during the course of an outbreak, on average, than those at the periphery. Unfortunately, mapping a whole network to identify central individuals who might be monitored for infection is typically very difficult. We propose an alternative strategy that does not require ascertainment of global network structure, namely, simply monitoring the friends of randomly selected individuals. Such individuals are known to be more central. To evaluate whether such a friend group could indeed provide early detection, we studied an H1N1 flu outbreak at Harvard College in late 2009. We followed 744 students who were either members of a group of randomly chosen individuals or a group of their friends. Based on clinical diagnoses, the progression of the epidemic in the friend group occurred 13.9 days (95% C.I. 9.9–16.6) in advance of the randomly chosen group (i.e., the population as a whole). The friend group also showed a significant lead time (p<0.05) on day 16 of the epidemic, a full 46 days before the peak in daily incidence in the population as a whole. This sensor method could provide significant additional time to react to epidemics in small or large populations under surveillance. The amount of lead time will depend on features of the outbreak and the network at hand. The method could in principle be generalized to other biological, psychological, informational, or behavioral contagions that spread in networks.
The Spread of Alcohol Consumption Behavior in a Large Social Network
Alcohol consumption has important health-related consequences and numerous biological and social determinants.
To explore quantitatively whether alcohol consumption behavior spreads from person to person in a large social network of friends, coworkers, siblings, spouses, and neighbors, followed for 32 years.
Longitudinal network cohort study.
The Framingham Heart Study.
12 067 persons assessed at several time points between 1971 and 2003.
Self-reported alcohol consumption (number of drinks per week on average over the past year and number of days drinking within the past week) and social network ties, measured at each time point.
Clusters of drinkers and abstainers were present in the network at all time points, and the clusters extended to 3 degrees of separation. These clusters were not only due to selective formation of social ties among drinkers but also seem to reflect interpersonal influence. Changes in the alcohol consumption behavior of a person's social network had a statistically significant effect on that person's subsequent alcohol consumption behavior. The behaviors of immediate neighbors and coworkers were not significantly associated with a person's drinking behavior, but the behavior of relatives and friends was.
A nonclinical measure of alcohol consumption was used. Also, it is unclear whether the effects on long-term health are positive or negative, because alcohol has been shown to be both harmful and protective. Finally, not all network ties were observed.
Network phenomena seem to influence alcohol consumption behavior. This has implications for clinical and public health interventions and further supports group-level interventions to reduce problematic drinking.
Alone in the Crowd: The Structure and Spread of Loneliness in a Large Social Network
The discrepancy between an individual's loneliness and the number of connections in a social network is well documented, yet little is known about the placement of loneliness within, or the spread of loneliness through, social networks. We use network linkage data from the population-based Framingham Heart Study to trace the topography of loneliness in people's social networks and the path through which loneliness spreads through these networks. Results indicated that loneliness occurs in clusters, extends up to three degrees of separation, is disproportionately represented at the periphery of social networks, and spreads through a contagious process. The spread of loneliness was found to be stronger than the spread of perceived social connections, stronger for friends than family members, and stronger for women than for men. The results advance our understanding of the broad social forces that drive loneliness and suggest that efforts to reduce loneliness in our society may benefit by aggressively targeting the people in the periphery to help repair their social networks and to create a protective barrier against loneliness that can keep the whole network from unraveling.
Partisanship, Voting, and the Dopamine D2 Receptor Gene
Previous studies have found that both political orientations (Alford, Funk and Hibbing 2005) and voting behavior (Fowler, Baker and Dawes 2008; Fowler and Dawes 2008) are significantly heritable. In this article we study genetic variation in another important political behavior: partisan attachment. Using the National Longitudinal Study of Adolescent Health, we show that individuals with the A2 allele of the D2 dopamine receptor gene are significantly more likely to identify as a partisan than those with the A1 allele. Further, we find that this gene's association with partisanship also mediates an indirect association between the A2 allele and voter turnout. These results are the first to identify a specific gene that may be partly responsible for the tendency to join political groups, and they may help to explain correlation in parent and child partisanship and the persistence of partisan behavior over time.
Dynamic Spread of Happiness in a Large Social Network:
Longitudinal Analysis Over 20 Years in the Framingham Heart Study
To evaluate whether happiness can spread from person to person and whether niches of happiness form within social networks.
Longitudinal social network analysis.
Framingham Heart Study social network.
4739 individuals followed from 1983 to 2003.
Main outcome measures
Happiness measured with validated four item scale; broad array of attributes of social networks and diverse social ties.
Clusters of happy and unhappy people are visible in the network, and the relationship between people's happiness extends up to three degrees of separation (for example, to the friends of one's friends' friends). People who are surrounded by many happy people and those who are central in the network are more likely to become happy in the future. Longitudinal statistical models suggest that clusters of happiness result from the spread of happiness and not just a tendency for people to associate with similar individuals. A friend who lives within a mile (about 1.6 km) and who becomes happy increases the probability that a person is happy by 25% (95% confidence interval 1% to 57%). Similar effects are seen in coresident spouses (8%, 0.2% to 16%), siblings who live within a mile (14%, 1% to 28%), and next door neighbours (34%, 7% to 70%). Effects are not seen between coworkers. The effect decays with time and with geographical separation.
People's happiness depends on the happiness of others with whom they are connected. This provides further justification for seeing happiness, like health, as a collective phenomenon.
Two Genes Predict Voter Turnout
Fowler, Baker, and Dawes (2008) recently showed in two independent studies of twins that voter turnout has very high heritability. Here we investigate two specific genes that may contribute to this heritability via their impact on neurochemical processes that influence social behavior. Using data from the National Longitudinal Study of Adolescent Health, we show that a polymorphism of the MAOA gene significantly increases the likelihood of voting. We also find evidence of a gene-environment interaction between religious attendance and a polymorphism of the 5HTT gene that significantly increases voter turnout. These are the first results to ever link specific genes to political behavior and they suggest that political scientists should take seriously the claim that at least some variation in political behavior is due to innate predispositions.
The Colbert Bump in Campaign Donations: More Truthful Than Truthy
Stephen Colbert, the host of Comedy Central's The Colbert Report, claims that politicians who appear on his show will become more popular and are more likely to win elections. Although online discussions cite anecdotal evidence in support of his claim, it has never been scrutinized scientifically. In this article I use "facts" (sorry, Stephen) provided by the Federal Election Commission to create a matched control group of candidates who have never appeared on The Colbert Report. I then compare the personal campaign donations they receive to those received by candidates who have appeared on the program's segment "Better Know a District." The results show that Democratic candidates who appear on the Report receive a statistically significant "Colbert bump" in campaign donations, raising 44% more money in a 30-day period after appearing on the show. However, there is no evidence of a similar boost for Republicans. These results constitute the first scientific evidence of Stephen Colbert's influence on political campaigns.
Genetic Variation in Political Participation
The decision to vote has puzzled scholars for decades. Theoretical models predict little or no variation in participation in large population elections and empirical models have typically explained only a relatively small portion of individual-level variance in turnout behavior. However, these models have not considered the hypothesis that part of the variation in voting behavior can be attributed to genetic effects. Matching public voter turnout records in Los Angeles to a twin registry, we study the heritability of political behavior in monozygotic and dizygotic twins. The results show that genes account for a significant proportion of the variation in voter turnout. We also replicate these results with data from the National Longitudinal Study of Adolescent Health and show that they extend to a broad class of acts of political participation. These are the first findings to suggest that humans exhibit genetic variation in their tendency to participate in political activities.
The Collective Dynamics of Smoking in a Large Social Network
The prevalence of smoking has decreased substantially in the United States over the past 30 years. We examined the extent of the person-to-person spread of smoking behavior and the extent to which groups of widely connected people quit together.
We studied a densely interconnected social network of 12,067 people assessed repeatedly from 1971 to 2003 as part of the Framingham Heart Study. We used network analytic methods and longitudinal statistical models.
Discernible clusters of smokers and nonsmokers were present in the network, and the clusters extended to three degrees of separation. Despite the decrease in smoking in the overall population, the size of the clusters of smokers remained the same across time, suggesting that whole groups of people were quitting in concert. Smokers were also progressively found in the periphery of the social network. Smoking cessation by a spouse decreased a person's chances of smoking by 67% (95% confidence interval [CI], 59 to 73). Smoking cessation by a sibling decreased the chances by 25% (95% CI, 14 to 35). Smoking cessation by a friend decreased the chances by 36% (95% CI, 12 to 55 ). Among persons working in small firms, smoking cessation by a coworker decreased the chances by 34% (95% CI, 5 to 56). Friends with more education influenced one another more than those with less education. These effects were not seen among neighbors in the immediate geographic area.
Network phenomena appear to be relevant to smoking cessation. Smoking behavior spreads through close and distant social ties, groups of interconnected people stop smoking in concert, and smokers are increasingly marginalized socially. These findings have implications for clinical and public health interventions to reduce and prevent smoking.
The Authority of Supreme Court Precedent
We construct the complete network of 30,288 majority opinions written by the U.S. Supreme Court and the cases they cite from 1754 to 2002 in the United States Reports. Data from this network demonstrates quantitatively the evolution of the norm of stare decisis in the 19th Century and a significant deviation from this norm by the activist Warren court. We further describe a method for creating authority scores using the network data to identify the most important Court precedents. This method yields rankings that conform closely to evaluations by legal experts, and even predicts which cases they will identify as important in the future. An analysis of these scores over time allows us to test several hypotheses about the rise and fall of precedent. We show that reversed cases tend to be much more important than other decisions, and the cases that overrule them quickly become and remain even more important as the reversed decisions decline. We also show that the Court is careful to ground overruling decisions in past precedent, and the care it exercises is increasing in the importance of the decision that is overruled. finally, authority scores corroborate qualitative assessments of which issues and cases the Court prioritizes and how these change over time.
Click here to access the Supreme Court network data.
The Spread of Obesity in a Large Social Network Over 32 Years
The prevalence of obesity has increased substantially over the past 30 years. We performed a quantitative analysis of the nature and extent of the person-to-person spread of obesity as a possible factor contributing to the obesity epidemic.
We evaluated a densely interconnected social network of 12,067 people assessed repeatedly from 1971 to 2003 as part of the Framingham Heart Study. The body-mass index was available for all subjects. We used longitudinal statistical models to examine whether weight gain in one person was associated with weight gain in his or her friends, siblings, spouse, and neighbors.
Discernible clusters of obese persons were present in the network at all time points, and the clusters extended to three degrees of separation. These clusters did not appear to be solely attributable to the selective formation of social ties among obese persons. A person's chances of becoming obese increased by 57% (95% confidence interval [CI], 6 to 123) if he or she had a friend who became obese in a given interval. Among pairs of adult siblings, if one sibling became obese, the chance that the other would become obese increased by 40% (95% CI, 21 to 60). If one spouse became obese, the likelihood that the other spouse would become obese increased by 37% (95% CI, 7 to 73). These effects were not seen among neighbors in the immediate geographic location. Persons of the same sex had relatively greater influence on each other as compared with those of the opposite sex. The spread of smoking cessation did not account for the spread of obesity in the network.
Network phenomena appear to be relevant to the biologic and behavioral trait of obesity, and obesity appears to spread through social ties. These findings have implications for clinical and public health interventions.
Cosponsorship Networks in the U.S. House and Senate
Using large-scale network analysis I map the cosponsorship networks of all 280,000 pieces of legislation proposed in the U.S. House and Senate from 1973 to 2004. In these networks, a directional link can be drawn from each cosponsor of a piece of legislation to its sponsor. I use a number of statistics to describe these networks such as the quantity of legislation sponsored and cosponsored by each legislator, the number of legislators cosponsoring each piece of legislation, the total number of legislators who have cosponsored bills written by a given legislator, and network measures of closeness, betweenness, and eigenvector centrality. I then introduce a new measure I call "connectedness" which uses information about the frequency of cosponsorship and the number of cosponsors on each bill to make inferences about the social distance between legislators. Connectedness predicts which members will pass more amendments on the floor, a measure that is commonly used as a proxy for legislative influence. It also predicts roll call vote choice even after controlling for ideology and partisanship.
Click here to access the cosponsorship network data.
Dynamic Parties and Social Turnout: An Agent-Based Model
The authors develop an agent-based model of dynamic parties with social turnout built upon developments in different fields within social science. This model yields significant turnout, divergent platforms, and numerous results consistent with the rational calculus of voting model and the empirical literature on social turnout. In a simplified version of the model, the authors show how a local imitation structure inherently yields dynamics that encourage positive turnout. The model also generates new hypotheses about the importance of social networks and citizen-party interactions.
Turnout in a Small World
This chapter investigates between-voter interactions in a social network model of turnout. It shows that if 1) there is a small probability that voters imitate the behavior of one of their acquaintances, and 2) individuals are closely connected to others in a population (the "small-world" effect), then a single voting decision may affect dozens of other voters in a "turnout cascade." If people tend to be ideologically similar to other people they are connected to, then these turnout cascades will produce net favorable results for their favorite candidate. By changing more than one vote with one's own turnout decision, the turnout incentive is thus substantially larger than previously thought. We analyze conditions that are favorable to turnout cascades and show that the effect is consistent with real social network data from Huckfeldt and Sprague's South Bend and Indianapolis-St. Louis election surveys. We also suggest that turnout cascades may help explain over-reporting of turnout and the ubiquitous belief in a duty to vote.
James was recently named a Fellow of the John Simon Guggenheim Foundation, one of Foreign Policy's Top 100 Global Thinkers, TechCrunch's Most Innovative People in Democracy, and Most Original Thinker of the year by The McLaughlin Group. He has also been on The Colbert Report.
James's research on genopolitics with Chris Dawes has been featured in New York Times Magazine's Year in Ideas. His work on overconfidence with Dom Johnson has been featured in Discover Magazine's Year in Science. And his research on social networks with Nicholas Christakis has been featured in Time's Year in Medicine (twice), and in Harvard Business Review's Breakthrough Business Ideas.
Science magazine dubbed Christakis and Fowler the "dynamic duo" (though James thinks Nicholas makes a better Adam West). Together they have written a book on social networks for a general audience called Connected. Winner of a Books for a Better Life Award, it has been translated into twenty languages, named an Editor's Choice by the New York Times Book Review, and featured in Wired, Oprah's Reading Guide, Business Week's Best Books of the Year, GOOD's 15 Books You Must Read, and a cover story in New York Times Magazine.
The physicist and the political scientist discuss contagion and the Obama campaign, debate the natural selection of robustness and ask whether society is turning inward.
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