The authors distinguish between emotions that operate primarily in dyadic relationships and emotions that operate in a significant manner in collective contexts. The authors examine the evolutionary role each emotion and cite research about ways these emotions might contribute to the creation and maintenance of cooperative behaviors: "This chapter is premised on the claim that human cooperation is profoundly shaped by, and perhaps only possible because of, emotions. We will examine the manner in which different emotions shape behavior in cooperative contexts…Although framed within an evolutionary psychological perspective, our goal is not to present definitive evidence of the validity of this particular approach, but rather to spur future investigations of the role of emotions in cooperation. Toward that end, on an emotion-by-emotion basis we will both briefly describe a variety of existing findings and present a number of hypotheses, specifying discrete, testable predictions whenever possible."

Emotions that are primarily dyadic include romantic love, gratitude, anger, envy, jealousy, guilt righteousness and contempt. Romantic love is seen as a means of overcoming a barrier to the kind of cooperation we see in parenting -– the temptation to defect in the short term on a relationship that requires a long-term investment. "A number of investigators have suggested that some emotions can be understood as mechanisms design to commit people to behavior that yields long-term payoffs, thus overcoming the temptation for short-term defection. Romantic love, a universal human emotion that underpins pair bonding, appears to be such a mechanism."

Where romantic love is about how one feels about another person, gratitude addresses how one feels about somebody's behavior, and can be an emotional currency that binds one to reciprocity. "Gratitude focuses both attention and a positive, affiliative orientation on a party who has supplied the actor with a substantial benefit. In the context of its initial elicitation, gratitude seems to prompt the actor to recognize a valuable interaction partner and subsequently signal a willingness to reciprocate."

Why do people get so angry when someone cuts ahead of them in a queue or in traffic? This is clue to the evolutionary advantage of anger as a means of protecting ones own interests, but when it comes to the thus-far unexplained human propensity to punish cheaters, even at a cost to themselves, anger might be instrumental in conferring advantage to a group that requires monitoring and sanction of free riders in order to maintain a public good or create an institution for collective action: "If gratitude is elicited by receipt of a benefit, its opposite is anger, elicited by actual ar attempted exploitation or harm. More formally, anger is the response to the infliction of a cost. In addition to showing an "irrational" willingness to reward generosity, subjects in behavioral economics experiments also show an eagerness to punish uncooperative partners…Together, these results clearly demonstrate that even within the confines of finite anonymous games, angry individuals often place paramount importance on harming the transgressor, and are willing to incur substantial costs in order to do so."

The Institutional Analysis and Development (IAD) framework developed by the Ostroms and their colleagues at Indiana University provides a foundation for studying a multitude of theories, models, and predictions of public choice behaviors in different systems of governance and organization.

Frameworks define the action arena to which it would be applied; the resulting patterns of interactions and outcomes, and the means of evaluating those outcomes.

A framework is a general language about how varying rules, physical and material conditions, and attributes of a community affect the structure of action arenas, the incentives for actors, and resulting outcomes.

Action arenas include an action situation and the actors in that situation.

An action situation includes:

• Participants
• Positions
• Outcomes
• Action-outcome linkages
• Control that participants exercise
• Information
• Cost and benefits of outcomes

Actors (individual or corporate) involve:

• Resources brought to the situation
• Values assigned to states of the world
• Methods for dealing with knowledge and information
• Selection processes for courses of action

Analysts can make strong predictions in tightly constrained situations of complete information: overuse of resources in an open commons where the actors do not share access to collective choice arenas.

Results are not as clear in situations where actors are embedded in communities with norms of fairness and conservation as well as the ability to communicate with each other.

Evaluation criteria can include a range of values for categories such as the following:

• Economic efficiency
• Fiscal equity among actors
• Redistributional equity (e.g., policies to care for poorer individuals
• Accountability
• Conformance to a general morality
• Adaptability to change

The IAD framework has been applied to various domains to make predictions of resulting behaviors in field settings. Examples of successful application include:

• Police services
• Urban public services in general
• Common-pool resources: these were studied in laboratory as well as field settings. The IAD framework was used to create a theory of behavior. Communication of participants affects behavior: if no communication was permitted, the results approximated that of non-cooperative game theory. Communication led to different, more positive, results.
• The IAD framework was used to develop extensive databases coding common-pool resources and diverse property regimes.

Six Degrees begins in the beginning. Stanley Milgram's initial small world studies are analyzed. His findings in seeing if a group of people in Nebraska can get a letter to someone in Massachusetts are scrutinized. Milgram left a puzzle. Mathematically, six degrees of separation can be shown and intuitively it is appealing. But do social networks actually work that way?

Initially, Watts steps into the world of pure mathematic theory. Graph theory and random graphs are employed to build potential worlds in which connections can be made. These tools are detailed and their histories explained.

Watts and his colleagues then take the science to new levels, by introducing sociology, epidemiology, economics, and business models into this new multi-disciplinary science. Immediately, each new field of study brings with it new insights into network dynamics.

This convergence of disciplines reveals the social, transportation and technological networks that make up our world. These networks are, ultimately, made up of individuals. Individuals in turn relate back to the networks and define how they operate.

Socially, people relate to their network by clustering. Clusters are logical organizations of network elements. In a social context, we might cluster in terms of a religion, a favorite author, a school we are attending or an affinity for a type of food. Some of these have very close physical distance, while others have a social distance with members spread out over a large area.

Networks of this type are, to various extents, “scale-free” networks. If graphed these networks roughly follow a classic power law trend where the level of connectivity between two nodes in a network increases dramatically as more nodes are connected. Real-world scale-free networks tend to have highly connected hubs which rapidly, purposely, and efficiently transmit pertinent or pervasive content from one location to another. In social circles, these are networkers. In the airline network these are hub airports. In traffic they would be freeway interchanges.

Due to this architecture, the Internet and modern air transport have combined to greatly decrease the role of proximity in our social networks. This has had great impacts on commerce, tourism, cultural sensitivity and other social factors. However, it has also led to great risks in the transmission of diseases, sensitivity to distant economic fluctuations, and rapid spread of misinformation.

These dynamics create a type of network that Duncan calls simultaneously robust and vulnerable. Their strength and weakness is that, with rapid transmission from cluster to cluster, anything can move quickly from one location or group to another. He uses the example of Toyota, whose network of suppliers was organized in such a way as to quickly compensate for and recover from a potential economic catastrophe.

Stable scale-free networks do not rely on a rigid hierarchy to provide direction in times of crisis. Rather, the structure of the network itself can rapidly respond to an unforeseen situation.

Their network was arranged in such a way as to foster and reward communication. This communication helped cope with ambiguous or unplanned situations. Rather than paralyzing Toyota while people waited for a decision from a rigid hierarchy, the contractors in the network were able to analyze the calamity and provide a rapid response to it.

As mentioned above, this robustness also rapidly transmits malicious content as well. The Melissa Virus, SARS and Ebola are analyzed to show why the network did or did not transmit them and, when it did, how they eventually died out.

Watts ends this book by summarizing that the multidimensional nature of social distance is sometimes counterintuitive and subjective. People can feel close in a network sense to people they are physically distant from and, conversely, socially distant from people physically nearby.

He continues by warning that social and physical distances have shrunk. People can quickly travel from place to place and economies are highly interdependent. The sheer number of dependencies in the modern world may yield surprising results from seemingly insignificant actions.

He finishes by showing the stability of our networks with the example of how New York adapted to the 9-11 attacks. The City bounced back to semi-normal operations within a week. During the disaster, the best laid plans of emergency operations staff were scuttled by the utter unavailability of facilities and services designed to copy with disasters. The network will provide.

Social psychological research has a long tradition of interest in cooperative behavior and commons dilemmas, beginning with Von Neumann and Morgenstern's 1944 book, Theory of Games and Economic Behavior. It is convenient to summarize the way psychological studies have attacked the commons problem through nine variables (social motives, gender, payoff structure, uncertainty, power, status, group size, communication, causes, frames) divided into three groups (individual differences, situational factors of the task structure, and the perceived effects of situational factors.) Although behavior elicited in a controlled lab environment is never the same as that observed in field research, lab research is an indispensable tool for teasing out causal relations from the larger number of interacting influences. Attention to the findings of psychological research relevant to the specific instance of a commons dilemma can make the difference in generating positive collective action.

Studies on social motives have found correlations between motives and choice behavior and interpretation of others' behavior. Liebrand et al. (1986) demonstrated that "people with individualist social motives tend to interpret behavior along the might dimension (what works), whereas cooperators tend to view cooperation and competition as varying on the moral dimension (what is good or bad)." Less intuitive findings have come out of research into social rewards for cooperative behavior. Gachter and Fehr (1999) conducted a study around public goods dilemmas with an anonymous group, a group that met beforehand to establish a group identity, a group that had a chance to interact after playing, and a group that met before and after. They found that neither the second nor the third groups had significant improvements in cooperation, but that the fourth option resulted in "significantly higher levels of contribution."

Uncertainty of resource size may play a detrimental role in commons dilemmas for multiple reasons. Any factor which threatens to bring an end to the resource will decrease interest in one's reputation and therefore with the relations that support the resource's maintenance. Uncertainty also helps diffuse personal responsibility, since overusers can try to justify their actions through their ignorance of the current resource size.

Experimenters have also uncovered interesting effects from varying groups size on self-efficacy, an individual's sense of their own competence in taking effective action. Smaller groups were found by Kerr (1989) to have higher averages when testing "collective" efficacy, the sense that the group could carry out effective actions to achieve a desired outcome. In groups with a relatively low provision point, the percentage of cooperating members necessary to support the public good, small group size was associated with a sense of "collective" efficacy.

Voting can significantly improve efficiencies in commons dilemmas by acting as a form of communication. Collective learning of general information "extends to subsequent situations and enables people to coordinate their activities even in rounds when no proposals are made."

Evolutionary psychology has been portrayed as justifying or implying a lot of bad ideas in the 20th century, but it need not suffer from these mistaken linkages and can potentially shed light on how to build better social institutions. Although the claim has been made, evolutionary psychology is not consistent with the tenets of Social Darwinism. Whether a trait or behavior survives the process of natural or cultural selection has no bearing over our discourse on whether it is morally justified. Nor does it mean that we are determined like machines to act out these behaviors in every case, a theory termed 'behavioral determinism' by those criticizing evolutionary psychology or its earlier form, sociobiology. Any reputable biologist, or sociobiologist, would acknowledge that the fitness of a behavioral trait is dependent on the interaction between that trait and a given environment, so saying that a certain psychological predisposition in humans is the product of an evolutionary process does not mean that it is good, justifiable or useful in the world we live in. Evolutionary science stresses that fitness is fundamentally contingent. Furthermore, humans have a cultural inheritance that dictates in subtle ways how and when we should express or repress our behavioral traits, making the interaction between trait and environment even more complex. Evolutionary psychologists suggest that we pay close attention to the basic human behaviors that through cross-cultural analysis appear 'hard-wired', because it is these behaviors, such as sympathy for those in pain or identification with one's kin or tribe, that we want to either channel or suppress in order to reap the benefits of cooperation.

This article isolates four mechanisms that promote cooperation in the absence of a central authority: kin selection, cooperation for mutual advantage, reciprocal altruism, and group selection. Kin selection implies a kind of utilitarian genetic calculus, that sacrificing one's life for the right number of relatives will be favorable for one's genes. A sibling shares on average half of one's genes, so sacrificing one's life for two or more siblings makes evolutionary sense. An example of a behavior that might be explained by kin selection is the warning call of ground squirrels; a ground squirrel that notices a hawk circling will call out to warn its family, although it increases its likelihood of being noticed and eaten by the hawk. This form of cooperation requires enough brain or nose power to be able to determine who is a relative.

The second form, cooperation for mutual advantage, occurs when a particular given end (critical for survival) is easier to accomplish with a group working together. The quintessential example of this mechanism is group hunting; wolves (and our hunter-gatherer ancestors) hunt in packs because they will end up with a portion of the large game, which can be much larger than the small game they would be able to catch on their own and not have to share. This benefits of this mechanism is not as immediate or certain as those of kin selection, because the stronger hunters could potentially share nothing with the weak who helped. This article cites field studies of monkeys, lions, and fish, which show that group hunting generally only occurs when environmental conditions make it economically more efficient that hunting alone. While cooperation for mutual advantage is an important surplus-generating mechanism in nature, we should not expect this mechanism to form the basis of modern human cooperation. Modern human cooperation cannot be pared down to a single one-shot end, and it could be argued the developments of civilization we are most proud of, charity for the poor or sick, go against the logic of mutual advantage.

Reciprocal altruism looks similar to the mechanism of mutual advantage, except the benefits are spread over time rather than through a single interaction. One individual helps another individual with the expectation that in the future the gesture will be repaid. Reciprocal altruism works best when developed alongside "a large number of supplementary psychological and social institutions." Enduring reputation and social traditions such as gift-giving foster relationships of reciprocal altruism. This kind of a relationship requires a bigger brain to remember who gave you what and who has mooched off you for too long, but can generate a big societal payoff. "By allowing trade over a period of time, reciprocal altruism opens up the possibility of a division of labor and credit-based relationships. These innovations make possible the recognition of the gains from specialization, comparative advantage, and the insurance and risk-shifting elements of inter-temporal trade."

While reciprocal altruism is most compelling in small groups with face-to-face interaction, the final mechanism, group selection, treats populations as the unit of measure. Proponents of group selection argue that a population of individuals with altruistic traits would fare better than less altruistic populations, reaching the big payoffs described in the above paragraph. The traits in question could be genetically inherited or culturally inherited. Arguing for cultural group selection, "[g]roups that adopt 'better' cultural practices will again tend to grow healthier, wealthier, and more populous, gradually supplanting less efficient cultures through conquest, migration, or conscious adoption." This kind of cooperation requires even more specific conditions than the other three mechanisms. Because the scale of group selection is so much larger than the other mechanisms, it is still a controversial theory in natural and social sciences. The argument against cultural and biological group selection is based on problem of free riders without altruistic traits who might take advantage of the social surplus generated by their altruistic neighbors. While human populations have reached impressive levels of cooperation in modern societies, one can imagine natural disasters or devastating world wars that would eliminate the evolutionary strength of group selection.

The origins of deindividuation are found In LeBon’s crowd theory (1895/1995), who proposed that the psychological mechanisms of anonymity, suggestibility and contagion transform an assembly into a "psychological crowd." In the 1950’s it was argued that deindividuation occurs when individuals in a group are not paid attention to as individuals and that additional contextual factors (e.g. reductions of responsibility, arousal, sensory overload, etc.) played a part. In the 1970’s deindividuation theory became a popular focus of scientific research, however, the empirical support for deindividuation theory was weak. In fact there was virtually no evidence for the psychological state of deindividuation. In the 1980’s formulations of the theory focused on the psychological process of reduced (private) self-awareness as the defining feature of deindividuation.

Various studies have been conducted to empirically verify the theory, but evidence for deindividuation theory appears to be mixed. A recent meta-analysis study examined 60 tests of deindividuation theory and concluded that there is insufficient support for deindividuation. Disinhibition and anti-normative behavior are not more common in large groups and crowded anonymous settings. Moreover, there is no evidence that deindividuation is associated with reduced self-awareness, or even that reduced self-awareness increases disinhibition. Overall, then, deindividuation theory does not receive sufficient empirical support. More recent research suggests that groups are sensitive to normative cues associated with the social context. Thus, whereas deindividuation theory argues that the crowd causes a loss of identity, reverting the individual to irrationality, it seems more productive to reconceptualize deindividuation as a shift from a personal identity to a social identity, shared by members of the crowd.

The idea that behavior could be the result of local group norms was considered explicitly by Johnson and Downing (1979). Participants were made anonymous by means of mask and overalls reminiscent of the Ku Klux Klan or by means of nurses' uniforms. Although compared to the control condition, participants shocked somewhat more when dressed in the Ku Klux Klan uniforms, they actually shocked less when dressed as nurses. This finding illustrates that groups are sensitive to normative cues associated with the social context.

This latest finding lends weight to the idea that group behavior is closely tied to cultural identification. Further study in which participants are deliberately selected from specific cultural types might prove interesting.

Although Darwin's 19th century advocates stressed the role of competition in natural selection, Darwin established speculation about cultural evolution in regard to human cooperation: "It must not be forgotten that although a high standard of morality gives but slight or no advantage to each individual man and his children over other men of the tribe, yet that an increase in the number of well-endowed men and an advancement in the standard of morality will certainly give an immense advantage to one tribe over another. A tribe including many members who, from possessing in a high degree the spirit of patriotism, fidelity, obedience, courage, and sympathy, were always ready to aid one another, and to sacrifice for the common good, would be victorious over most other tribes; and t his would be natural selection."

The authors note that human social complexity is far beyond that of other social animals, and that biological mechanisms of kin selection and reciprocity are not adequate to fully explain human social behavior. Culture, defined as "information stored in individual brains (or in books and analogous media) that was acquired by imitation of, or teaching by others," has the properties of transmission forward through time and selection of successful strategies in common with genetic evolution. As Homo sapiens evolved, the mental and social capacity for cooperative work was highly adaptive for groups of small, relatively weak creatures with neither fangs nor claws nor wings. "Social instincts" enabled humans to band together in groups larger than the 50 individuals that our brain size allows in other primates. But that made cultural transmission of learning possible, which over-rode genetic group selection.

Although the Pleistocene era, with its radical climate changes, could have exerted long-term pressure on genetic group selection, the rapid evolution of social complexity over the past 10,000 years has not been long enough for significant genetic selection. Culture is both enabled by genetically-shaped human sociality, and is a means of progressively ratcheting mutually beneficial social cooperation. Once sociality, learning, and symbolic media make it possible to externalize and transmit individual learning, cooperative invention changes the game. Individual innovators can gain advantage through prestige and reputation, but only by displaying what they know, while learning and innovation enable the entire tribe to benefit from their innovations.

Culture harnesses and channels social instincts, enabling the creation of institutions. Norms enable the diffusion of enforcement of altruistic punishment through the population, leveraging emotions such as anger and shame to guard against free-riding, defection, and exploitation.