Editing Collective action (section)

===Methods and techniques===

Due to the interdisciplinary nature of both the mechanisms as well as the applications of spontaneous consensus, a variety of techniques have been developed to study the emergence and evolution of spontaneous cooperation. Two of the most widely used are [[game theory]] and [[social network analysis]].

====Game theory====

Traditionally [[game theory]] has been used to study [[zero-sum games]] but has been extended to many [[game theory#Game types|different types of games]]. Relevant to the study of spontaneous consensus are [[cooperative game theory|cooperative]] and [[non-cooperative game theory|non-cooperative]] games. Since a consensus must be reached without the presence of any external authoritative institution for it to be considered ''spontaneous'', non-cooperative games and [[Nash equilibrium]] have been the dominant paradigm for which to study its emergence.

In the context of non-cooperative games, a consensus is a formal Nash equilibrium that all players tend towards through [[self-enforcing agreement|self-enforcing]] alliances or agreements.

An important case study of the underlying mathematical dynamics is the [[coordination game]]. Even when coordination is desired, it can be difficult to achieve due to incomplete information and constrained time horizons.

====Social network analysis====

An alternative approach to studying the emergence of spontaneous consensus—that avoids many of the unnatural or overly constrained assumptions of game theoretic models—is the use of network based methods and social network analysis (SNA). These SNA models are theoretically grounded in the communication mechanism<ref name="ReferenceA"/> of facilitating consensus and describe its emergence through the information propagation processes of the network ([[behavioral contagion]]). Through the spread of influence (and ideas) between agents participating in the consensus, local and global consensus can emerge if the agents in the network achieve a shared equilibrium state. Leveraging this model of consensus, researchers have shown that local peer influence can be used to reach a global consensus and cooperation across the entire network.<ref>{{cite journal |last1=Mani |first1=Ankur |last2=Rahwan |first2=Iyad |last3=Pentland |first3=Alex |date=2013 |title=Inducing Peer Pressure to Promote Cooperation |journal=Scientific Reports |volume=3 |issue=1735 |pages=1735 |doi=10.1038/srep01735 |pmid=23619166 |pmc=3636514 |bibcode=2013NatSR...3.1735M }}</ref> While this model of consensus and cooperation has been shown to be successful in certain contexts, research suggest that communication and social influence cannot be fully captured by simple contagion models<ref>{{cite journal |last1=Alshamsi |first1=Aamena |last2=Pianesi |first2=Fabio |last3=Lepri |first3=Bruno |last4=Pentland |first4=Alex |last5=Rahwan |first5=Iyad |date=2015 |title=Beyond Contagion: Reality Mining Reveals Complex Patterns of Social Influence |journal=PLOS ONE |volume=10 |issue=8 |doi=10.1371/journal.pone.0135740 |pmid=26313449 |pmc=4551670 |page=e0135740|arxiv=1507.04192 |bibcode=2015PLoSO..1035740A |doi-access=free }}</ref> and as such a pure contagion based model of consensus may have limits.