The Spontaneous Emergence of Social Influence in Online Systems

Social influence drives both offline and online human behaviour. It pervades cultural markets, and manifests itself in the adoption of scientific and technical innovations as well as the spread of social practices. Prior empirical work on the diffusion of innovations in spatial regions or social networks has largely focused on the spread of one particular technology among a subset of all potential adopters. It has also been difficult to determine whether the observed collective behaviour is driven by natural influence processes, or whether it follows external signals such as media or marketing campaigns. Here, we choose an online context that allows us to study social influence processes by tracking the popularity of a complete set of applications installed by the user population of a social networking site, thus capturing the behaviour of all individuals who can influence each other in this context. By extending standard fluctuation scaling methods, we analyse the collective behaviour induced by 100 million application installations, and show that two distinct regimes of behaviour emerge in the system. Once applications cross a particular threshold of popularity, social influence processes induce highly correlated adoption behaviour among the users, which propels some of the applications to extraordinary levels of popularity. Below this threshold, the collective effect of social influence appears to vanish almost entirely in a manner that has not been observed in the offline world. Our results demonstrate that even when external signals are absent, social influence can spontaneously assume an on-off nature in a digital environment. It remains to be seen whether a similar outcome could be observed in the offline world if equivalent experimental conditions could be replicated

Persistence of social signatures in human communication

The social network maintained by a focal individual, or ego, is intrinsically dynamic and typically exhibits some turnover in membership over time as personal circumstances change. However, the consequences of such changes on the distribution of an ego’s network ties are not well understood. Here we use a unique 18-mo dataset that combines mobile phone calls and survey data to track changes in the ego networks and communication patterns of students making the transition from school to university or work. Our analysis reveals that individuals display a distinctive and robust social signature, captured by how interactions are distributed across different alters. Notably, for a given ego, these social signatures tend to persist over time, despite considerable turnover in the identity of alters in the ego network. Thus, as new network members are added, some old network members either are replaced or receive fewer calls, preserving the overall distribution of calls across network members. This is likely to reflect the consequences of finite resources such as the time available for communication, the cognitive and emotional effort required to sustain close relationships, and the ability to make emotional investments

Unlocking value for a circular economy through 3D printing: A research agenda

The circular economy (CE) aims to radically improve resource efficiency by eliminating the concept of waste and leading to a shift away from the linear take-make-waste model. In a CE, resources are flowing in a circular manner either in a biocycle (biomass) or technocycle (inorganic materials). While early studies indicate that 3D printing (3DP) holds substantial promise for sustainability and the creation of a CE, there is no guarantee that it will do so. There is great uncertainty regarding whether the current trajectory of 3DP adoption is creating more circular material flows or if it is leading to an alternative scenario in which less eco-efficient localised production, demands for customised goods, and a higher rate of product obsolescence combine to bring about increased resource consumption. It is critical that CE principles are embedded into the new manufacturing system before the adoption of 3DP reaches a critical inflection point in which negative practices become entrenched. This paper, authored by both academic and industry experts, proposes a research agenda to determine enablers and barriers for 3DP to achieve a CE. We explore the two following overarching questions to discover what specific issues they entail: (1) How can a more distributed manufacturing system based on 3DP create a circular economy of closed-loop material flows? (2) What are the barriers to a circular 3D printing economy? We specifically examine six areas-design, supply chains, information flows, entrepreneurship, business models and education-with the aim of formulating a research agenda to enable 3DP to reach its full potential for a CE

Statistically validated networks in bipartite complex systems

Many complex systems present an intrinsic bipartite nature and are often described and modeled in terms of networks [1-5]. Examples include movies and actors [1, 2, 4], authors and scientific papers [6-9], email accounts and emails [10], plants and animals that pollinate them [11, 12]. Bipartite networks are often very heterogeneous in the number of relationships that the elements of one set establish with the elements of the other set. When one constructs a projected network with nodes from only one set, the system heterogeneity makes it very difficult to identify preferential links between the elements. Here we introduce an unsupervised method to statistically validate each link of the projected network against a null hypothesis taking into account the heterogeneity of the system. We apply our method to three different systems, namely the set of clusters of orthologous genes (COG) in completely sequenced genomes [13, 14], a set of daily returns of 500 US financial stocks, and the set of world movies of the IMDb database [15]. In all these systems, both different in size and level of heterogeneity, we find that our method is able to detect network structures which are informative about the system and are not simply expression of its heterogeneity. Specifically, our method (i) identifies the preferential relationships between the elements, (ii) naturally highlights the clustered structure of investigated systems, and (iii) allows to classify links according to the type of statistically validated relationships between the connected nodes.Comment: Main text: 13 pages, 3 figures, and 1 Table. Supplementary information: 15 pages, 3 figures, and 2 Table

Antibiotic knowledge, attitudes, and practices: new insights from cross-sectional rural health behaviour surveys in low- and middle-income South-East Asia

Introduction: Low- and middle-income countries (LMICs) are crucial in the global response to antimicrobial resistance (AMR), but diverse health systems, healthcare practices, and cultural conceptions of medicine can complicate global education and awareness-raising campaigns. Social research can help understand LMIC contexts but remains underrepresented in AMR research. Objective: To (1) describe antibiotic-related knowledge, attitudes, and practices of the general population in two LMICs and to (2) assess the role of antibiotic-related knowledge and attitudes on antibiotic access from different types of healthcare providers. Design: Observational study: cross-sectional rural health behaviour survey, representative on the population level. Setting: General rural population in Chiang Rai (Thailand) and Salavan (Lao PDR), surveyed between November 2017 and May 2018. Participants: 2141 adult members (≥18 years) of the general rural population, representing 712,000 villagers. Outcome measures: Antibiotic-related knowledge, attitudes, and practices across sites and healthcare access channels. Findings: Villagers were aware of antibiotics (Chiang Rai: 95.7%; Salavan: 86.4%; p<0.001) and drug resistance (Chiang Rai: 74.8%; Salavan: 62.5%; p<0.001), but the usage of technical concepts for antibiotics was dwarfed by local expressions like “anti-inflammatory medicine” in Chiang Rai (87.6%; 95% confidence interval [CI]: 84.9–90.0) and “ampi” in Salavan (75.6%; 95% CI: 71.4–79.4). Multivariate linear regression suggested that attitudes against over-the-counter antibiotics were linked to 0.12 additional antibiotic use episodes from public healthcare providers in Chiang Rai (95% CI: 0.01 – 0.23) and 0.53 in Salavan (95% CI: 0.16 – 0.90). Conclusions: Locally specific conceptions and counter-intuitive practices around antimicrobials can complicate AMR communication efforts and entail unforeseen consequences. Overcoming “knowledge deficits” alone will therefore be insufficient for global AMR behaviour change. We call for an expansion of behavioural AMR strategies towards “AMR-sensitive interventions” that address context-specific upstream drivers of antimicrobial use (e.g. unemployment insurance) and complement education and awareness campaigns

Happy Aged People Are All Alike, While Every Unhappy Aged Person Is Unhappy in Its Own Way

Aging of the world's population represents one of the most remarkable success stories of medicine and of humankind, but it is also a source of various challenges. The aim of the collaborative cross-cultural European study of adult well being (ESAW) is to frame the concept of aging successfully within a causal model that embraces physical health and functional status, cognitive efficacy, material security, social support resources, and life activity. Within the framework of this project, we show here that the degree of heterogeneity among people who view aging in a positive light is significantly lower than the degree of heterogeneity of those who hold a negative perception of aging. We base this conclusion on our analysis of a survey involving 12,478 people aged 50 to 90 from six West European countries. We treat the survey database as a bipartite network in which individual respondents are linked to the actual answers they provide. Taking this perspective allows us to construct a projected network of respondents in which each link indicates a statistically validated similarity of answers profile between the connected respondents, and to identify clusters of individuals independently of demographics. We show that mental and physical well-being are key factors determining a positive perception of aging. We further observe that psychological aspects, like self-esteem and resilience, and the nationality of respondents are relevant aspects to discriminate among participants who indicate positive perception of aging

A simple model of bipartite cooperation for ecological and organizational networks

In theoretical ecology, simple stochastic models that satisfy two basic conditions about the distribution of niche values and feeding ranges have proved successful in reproducing the overall structural properties of real food webs, using species richness and connectance as the only input parameters1, 2, 3, 4. Recently, more detailed models have incorporated higher levels of constraint in order to reproduce the actual links observed in real food webs5, 6. Here, building on previous stochastic models of consumer–resource interactions between species1, 2, 3, we propose a highly parsimonious model that can reproduce the overall bipartite structure of cooperative partner–partner interactions, as exemplified by plant–animal mutualistic networks7. Our stochastic model of bipartite cooperation uses simple specialization and interaction rules, and only requires three empirical input parameters. We test the bipartite cooperation model on ten large pollination data sets that have been compiled in the literature, and find that it successfully replicates the degree distribution, nestedness and modularity of the empirical networks. These properties are regarded as key to understanding cooperation in mutualistic networks8, 9, 10. We also apply our model to an extensive data set of two classes of company engaged in joint production in the garment industry. Using the same metrics, we find that the network of manufacturer–contractor interactions exhibits similar structural patterns to plant–animal pollination networks. This surprising correspondence between ecological and organizational networks suggests that the simple rules of cooperation that generate bipartite networks may be generic, and could prove relevant in many different domains, ranging from biological systems to human society11, 12, 13, 14

Able but unwilling to enforce: cooperative dilemmas in group lending

It is known that greater social cohesion increases a group’s ability to enforce cooperation. Despite this, defectors often go unpunished and groups with social structures that are a priori favorable often fail. A critical distinction is required between the structural effect on ability versus willingness to punish. We develop a theoretical framework in which variation in a group’s social structure generates a tension between ability and willingness to enforce cooperation. Structures that promote ability to punish also often reduce interest in carrying out sanctions, thus changing collective outcomes. Our empirical analysis involves a well-defined cooperative dilemma: group lending in Sierra Leone. We complement statistical modelling, based on a dataset containing 5,487 group repayments, with ethnographic analysis. We find: (1) Structural cohesion only increases economic cooperation between borrowers to a point, beyond which unwillingness outweighs increased ability to punish, reducing group repayments. (2) Groups with disconnected subgroups perform worse on average. Although borrowers are more willing to punish defectors in the out-subgroup, they are unable to do so effectively

Revisiting the complex adaptive systems paradigm: leading perspectives for researching operations and supply chain management issues

This paper presents a conceptual model for a renewed consideration of the complex adaptive systems (CAS) perspective in operations and supply chain management research. A literature review identifies the approaches taken in published research to examine issues such as complexity, adaptation, and emergent behavior. We present a revised conceptual framework that offers directions for embracing key tenets from CAS research so as to gain deeper insights into pertinent issues within the field. We introduce the articles that are part of this special issue and highlight how these articles relate to the conceptual framework proposed in the paper. We also propose some methodological directions that can help in undertaking rigorous investigations of some important aspects that have theoretical and managerial significance