Collaboration in Social Networks

The very notion of social network implies that linked individuals interact repeatedly with each other. This allows them not only to learn successful strategies and adapt to them, but also to condition their own behavior on the behavior of others, in a strategic forward looking manner. Game theory of repeated games shows that these circumstances are conducive to the emergence of collaboration in simple games of two players. We investigate the extension of this concept to the case where players are engaged in a local contribution game and show that rationality and credibility of threats identify a class of Nash equilibria -- that we call "collaborative equilibria" -- that have a precise interpretation in terms of sub-graphs of the social network. For large network games, the number of such equilibria is exponentially large in the number of players. When incentives to defect are small, equilibria are supported by local structures whereas when incentives exceed a threshold they acquire a non-local nature, which requires a "critical mass" of more than a given fraction of the players to collaborate. Therefore, when incentives are high, an individual deviation typically causes the collapse of collaboration across the whole system. At the same time, higher incentives to defect typically support equilibria with a higher density of collaborators. The resulting picture conforms with several results in sociology and in the experimental literature on game theory, such as the prevalence of collaboration in denser groups and in the structural hubs of sparse networks

A Social Network Approach to the Dual Aspect of Moral Competence

This work presents evidence supporting the relationship between the dual aspect of moral competence (emotion and cognition) and social networks in school settings. We conducted empirical research with 160 students from various disciplines of the social sciences and different cohorts in two Brazilian public universities. Firstly, the participants responded to Georg Lind’s Moral Competence Test (MCT-xt). Following this, a sociometric generator regarding relationships of friendship and collaboration in social networks was applied, and several Exponential Random Graphs Models (ERGMs), with the MCT-xt score as an exogenous effect and predictor of these relationships, were utilized. We also used a Crisp-Set Qualitative Comparative Analysis in order to determine if the cohorts, where the average MCT-xt was associated with the interactional structure, obeyed the same causal configuration. There exist two conditional configurations: (1) a sufficient score of MCT-xt in a social network with homogeneous status encourages a proactive search of collaboration; (2) an insufficient score of MCT-xt in a social network with homogeneous status encourages a collaborative exchange based on the popularity of some individuals. This work reveals how to interpret, at the grouping level, the results of MCT-xt

Gender Disparities in Science? Dropout, Productivity, Collaborations and Success of Male and Female Computer Scientists

Scientific collaborations shape ideas as well as innovations and are both the substrate for, and the outcome of, academic careers. Recent studies show that gender inequality is still present in many scientific practices ranging from hiring to peer-review processes and grant applications. In this work, we investigate gender-specific differences in collaboration patterns of more than one million computer scientists over the course of 47 years. We explore how these patterns change over years and career ages and how they impact scientific success. Our results highlight that successful male and female scientists reveal the same collaboration patterns: compared to scientists in the same career age, they tend to collaborate with more colleagues than other scientists, seek innovations as brokers and establish longer-lasting and more repetitive collaborations. However, women are on average less likely to adapt the collaboration patterns that are related with success, more likely to embed into ego networks devoid of structural holes, and they exhibit stronger gender homophily as well as a consistently higher dropout rate than men in all career ages

Networked professional learning

Sloep, P. B., & Rusman, E. (2013, 27-31 August). Networked Professional Learning. Symposium contribution to N. Pataraia & A. Margayan, Learning Through Networks, Symposium at the EARLI Conference for Research on Learning and Instruction, Responsible Teaching and Sustainable Learning, Munich, Germany.The article argues for the role that networked learning can play in professional development and illustrates this role through processes of trust building

The Use of Social Media in Gathering and Sharing Competitive Intelligence

Utilizing social media in the business context is an issue of growing interest. This article discusses how social media can contribute to information gathering and to information and knowledge sharing within a company in the context of competitive intelligence. The research is conducted as a systematic literature review. The results show that so far only a few journal articles have been published discussing these issues. They propose that social media applications can contribute to competitive intelligence activities more in sharing than gathering information and knowledge. The common benefit received from using different social media applications seems to be the added value compared to using more traditional knowledge sharing tools

A natural experiment of social network formation and dynamics

10.1073/pnas.1404770112Proceedings of the National Academy of Sciences of the United States of America112216595-660

Análise de conteúdo da comunicação assíncrona : considerações metodológicas e recomendações práticas

Disponível onlineNeste artigo discutimos o potencial e os desafios metodológicos que se colocam aos investigadores que pretendem analisar o conteúdo da comunicação assíncrona gerada em ambientes online. Trata-se de uma temática atual e pertinente num momento em que as instituições publicas e privadas se apoiam cada vez mais nas tecnologias digitais para o desenho de cenários de educação/formação online em se criam situações de aprendizagem ricas e diversificadas. Nestes novos ambientes é recorrente o uso da interação com predominância da comunicação escrita, e é pelo seu estudo que se consegue capturar os processos de construção do conhecimento e de colaboração gerados em contextos virtual. O presente artigo está organizado em quatro secções onde se analisa e discute as diferentes fases que integram a análise de conteúdo da comunicação mediada por computador (CMC), nomeadamente a escolha do modelo teórico e da unidade de análise bem como os procedimentos metodológicos que permitem assegurar a fiabilidade do processo de codificação da comunicação textual. A discussão é sustentada com a apresentação de um exemplo concreto no sentido de ajudar os investigadores a perceberem como a análise de conteúdo pode ser usada para compreender a complexidade dos processos de ensino e aprendizagem em ambientes online.In this article we discuss the potential and the methodological challenges posed to researchers who seek to analyse the content of asynchronous communication generated within online environments. It addresses a current and relevant issue, particularly in the context of higher education, in which the use of digital technologies opens up opportunities for the design of new online education/training scenarios. In those new learning environments, the use of interaction, predominantly written communication, is recurrent, thus being its study a way of investigating the processes of knowledge construction in virtual context. In the present article we begin by addressing the different stages occurring in the process of content analysis of computer-mediated communication (CMC), including the choice of the theoretical model and the unit of analysis, as well as the methodological procedures which allow to assure the reliability of the coding process of the written text generated in asynchronous interaction. The discussion is sustained by the presentation of a concrete example, in order to help researchers use the content analysis of asynchronous communication to understand the complexity of teaching and learning processes in online environments.FC

Self-regulation versus social influence for promoting cooperation on networks

Cooperation is a relevant and controversial phenomenon in human societies. Indeed, although it is widely recognized essential for tackling social dilemmas, finding suitable policies for promoting cooperation can be arduous and expensive. More often, it is driven by pre-established schemas based on norms and punishments. To overcome this paradigm, we highlight the interplay between the influence of social interactions on networks and spontaneous self-regulating mechanisms on individuals behavior. We show that the presence of these mechanisms in a prisoner’s dilemma game, may oppose the willingness of individuals to defect, thus allowing them to behave cooperatively, while interacting with others and taking conflicting decisions over time. These results are obtained by extending the Evolutionary Game Equations over Networks to account for self-regulating mechanisms. Specifically, we prove that players may partially or fully cooperate whether self-regulating mechanisms are sufficiently stronger than social pressure. The proposed model can explain unconditional cooperation (strong self-regulation) and unconditional defection (weak self-regulation). For intermediate selfregulation values, more complex behaviors are observed, such as mutual defection, recruiting (cooperate if others cooperate), exploitation of cooperators (defect if others cooperate) and altruism (cooperate if others defect). These phenomena result from dynamical transitions among different game structures, according to changes of system parameters and cooperation of neighboring players. Interestingly, we show that the topology of the network of connections among players is crucial when self-regulation, and the associated costs, are reasonably low. In particular, a population organized on a random network with a Scale-Free distribution of connections is more cooperative than on a network with an Erdös-Rényi distribution, and, in turn, with a regular one. These results highlight that social diversity, encoded within heterogeneous networks, is more effective for promoting cooperation