Large-scale analysis of micro-level citation patterns reveals nuanced selection criteria.

The analysis of citations to scientific publications has become a tool that is used in the evaluation of a researcher's work; especially in the face of an ever-increasing production volume1-6. Despite the acknowledged shortcomings of citation analysis and the ongoing debate on the meaning of citations7,8, citations are still primarily viewed as endorsements and as indicators of the influence of the cited reference, regardless of the context of the citation. However, only recently has attention9,10 been given to the connection between contextual information and the success of citing and cited papers, primarily because of the lack of extensive databases that cover both types of metadata. Here we address this issue by studying the usage of citations throughout the full text of 156,558 articles published by the Public Library of Science (PLoS), and by tracing their bibliometric history from among 60 million records obtained from the Web of Science. We find universal patterns of variation in the usage of citations across paper sections11. Notably, we find differences in microlevel citation patterns that were dependent on the ultimate impact of the citing paper itself; publications from high-impact groups tend to cite younger references, as well as more very young and better-cited references. Our study provides a quantitative approach to addressing the long-standing issue that not all citations count the same.

Humans display a reduced set of consistent behavioral phenotypes in dyadic games.

Socially relevant situations that involve strategic interactions are widespread among animals and humans alike. To study these situations, theoretical and experimental research has adopted a game theoretical perspective, generating valuable insights about human behavior. However, most of the results reported so far have been obtained from a population perspective and considered one specific conflicting situation at a time. This makes it difficult to extract conclusions about the consistency of individuals' behavior when facing different situations and to define a comprehensive classification of the strategies underlying the observed behaviors. We present the results of a lab-in-the-field experiment in which subjects face four different dyadic games, with the aim of establishing general behavioral rules dictating individuals' actions. By analyzing our data with an unsupervised clustering algorithm, we find that all the subjects conform, with a large degree of consistency, to a limited number of behavioral phenotypes (envious, optimist, pessimist, and trustful), with only a small fraction of undefined subjects. We also discuss the possible connections to existing interpretations based on a priori theoretical approaches. Our findings provide a relevant contribution to the experimental and theoretical efforts toward the identification of basic behavioral phenotypes in a wider set of contexts without aprioristic assumptions regarding the rules or strategies behind actions. From this perspective, our work contributes to a fact-based approach to the study of human behavior in strategic situations, which could be applied to simulating societies, policy-making scenario building, and even a variety of business applications.

Strategical incoherence regulates cooperation in social dilemmas on multiplex networks.

Cooperation is a very common, yet not fully-understood phenomenon in natural and human systems. The introduction of a network within the population is known to affect the outcome of cooperative dynamics, allowing for the survival of cooperation in adverse scenarios. Recently, the introduction of multiplex networks has yet again modified the expectations for the outcome of the Prisoner's Dilemma game, compared to the monoplex case. However, much remains unstudied regarding other social dilemmas on multiplex, as well as the unexplored microscopic underpinnings of it. In this paper, we systematically study the evolution of cooperation in all four games in the T-S plane on multiplex. More importantly, we find some remarkable and previously unknown features in the microscopic organization of the strategies, that are responsible for the important differences between cooperative dynamics in monoplex and multiplex. Specifically, we find that in the stationary state, there are individuals that play the same strategy in all layers (coherent), and others that don't (incoherent). This second group of players is responsible for the surprising fact of a non full-cooperation in the Harmony Game on multiplex, never observed before, as well as a higher-than-expected cooperation rates in some regions of the other three social dilemmas.

Social embeddedness in an online weight management programme is linked to greater weight loss.

The obesity epidemic is heightening chronic disease risk globally. Online weight management (OWM) communities could potentially promote weight loss among large numbers of people at low cost. Because little is known about the impact of these online communities, we examined the relationship between individual and social network variables, and weight loss in a large, international OWM programme. We studied the online activity and weight change of 22,419 members of an OWM system during a six-month period, focusing especially on the 2033 members with at least one friend within the community. Using Heckman's sample-selection procedure to account for potential selection bias and data censoring, we found that initial body mass index, adherence to self-monitoring and social networking were significantly correlated with weight loss. Remarkably, greater embeddedness in the network was the variable with the highest statistical significance in our model for weight loss. Average per cent weight loss at six months increased in a graded manner from 4.1% for non-networked members, to 5.2% for those with a few (two to nine) friends, to 6.8% for those connected to the giant component of the network, to 8.3% for those with high social embeddedness. Social networking within an OWM community, and particularly when highly embedded, may offer a potent, scalable way to curb the obesity epidemic and other disorders that could benefit from behavioural changes.

Adoption of a High-Impact Innovation in a Homogeneous Population.

Adoption of innovations, whether new ideas, technologies, or products, is crucially important to knowledge societies. The landmark studies of adoption dealt with innovations having great societal impact (such as antibiotics or hybrid crops) but where determining the utility of the innovation was straightforward (such as fewer side effects or greater yield). Recent large-scale studies of adoption were conducted within heterogeneous populations and focused on products with little societal impact. Here, we focus on a case with great practical significance: adoption by small groups of highly trained individuals of innovations with large societal impact but for which it is impractical to determine the true utility of the innovation. Specifically, we study experimentally the adoption by critical care physicians of a diagnostic assay that complements current protocols for the diagnosis of life-threatening bacterial infections and for which a physician cannot estimate the true accuracy of the assay based on personal experience. We show through computational modeling of the experiment that infection-spreading models-which have been formalized as generalized contagion processes-are not consistent with the experimental data, while a model inspired by opinion models is able to reproduce the empirical data. Our modeling approach enables us to investigate the efficacy of different intervention schemes on the rate and robustness of innovation adoption in the real world. While our study is focused on critical care physicians, our findings have implications for other settings in education, research, and business, where small groups of highly qualified peers make decisions about the adoption of innovations whose utility is difficult if not impossible to gauge.