the implication of social cognition for experimental economics From the issue entitled "Special issue on Experimental economics and the social embedding of economic behavior and cognition"

Can human social cognitive processes and social motives be grasped by the methods of experimental economics? Experimental studies of strategic cognition and social preferences contribute to our understanding of the social aspects of economic decisions making. Yet, papers in this issue argue that the social aspects of decision-making introduce several difficulties for interpreting the results of economic experiments. In particular, the laboratory is itself a social context, and in many respects a rather distinctive one, which raises questions of external validity.

Social approach in preschool children with Williams syndrome: the role of the face

Background Indiscriminate social approach behaviour is a salient aspect of the Williams syndrome (WS) behavioural phenotype. The present study examines approach behaviour in preschoolers with WS and evaluates the role of the face in WS social approach behaviour. Method Ten preschoolers with WS (aged 3-6 years) and two groups of typically developing children, matched to the WS group on chronological or mental age, participated in an observed play session. The play session incorporated social and non-social components including two components that assessed approach behaviour towards strangers, one in which the stranger’s face could be seen and one in which the stranger’s face was covered. Results In response to the non-social aspects of the play session, the WS group behaved similarly to both control groups. In contrast, the preschoolers with WS were significantly more willing than either control group to engage with a stranger, even when the stranger’s face could not be seen. Conclusion The findings challenge the hypothesis that an unusual attraction to the face directly motivates social approach behaviour in individuals with WS.

Considering the normative, systemic and procedural dimensions in indicator-based sustainability assessments in agriculture

This paper develops a framework for evaluating sustainability assessment methods by separately analyzing their normative, systemic and procedural dimensions as suggested by Wiek and Binder [Wiek, A, Binder, C. Solution spaces for decision-making – a sustainability assessment tool for city-regions. Environ Impact Asses Rev 2005, 25: 589-608.]. The framework is then used to characterize indicator-based sustainability assessment methods in agriculture. For a long time, sustainability assessment in agriculture has focused mostly on environmental and technical issues, thus neglecting the economic and, above all, the social aspects of sustainability, the multifunctionality of agriculture and the applicability of the results. In response to these shortcomings, several integrative sustainability assessment methods have been developed for the agricultural sector. This paper reviews seven of these that represent the diversity of tools developed in this area. The reviewed assessment methods can be categorized into three types: (i) top-down farm assessment methods; (ii) top-down regional assessment methods with some stakeholder participation; (iii) bottom-up, integrated participatory or transdisciplinary methods with stakeholder participation throughout the process. The results readily show the trade-offs encountered when selecting an assessment method. A clear, standardized, top-down procedure allows for potentially benchmarking and comparing results across regions and sites. However, this comes at the cost of system specificity. As the top-down methods often have low stakeholder involvement, the application and implementation of the results might be difficult. Our analysis suggests that to include the aspects mentioned above in agricultural sustainability assessment, the bottomup, integrated participatory or transdisciplinary methods are the most suitable ones.

Ontology modeling for generation of clinical pathways

Purpose: Increasing costs of health care, fuelled by demand for high quality, cost-effective healthcare has drove hospitals to streamline their patient care delivery systems. One such systematic approach is the adaptation of Clinical Pathways (CP) as a tool to increase the quality of healthcare delivery. However, most organizations still rely on are paper-based pathway guidelines or specifications, which have limitations in process management and as a result can influence patient safety outcomes. In this paper, we present a method for generating clinical pathways based on organizational semiotics by capturing knowledge from syntactic, semantic and pragmatic to social level. Design/methodology/approach: The proposed modeling approach to generation of CPs adopts organizational semiotics and enables the generation of semantically rich representation of CP knowledge. Semantic Analysis Method (SAM) is applied to explicitly represent the semantics of the concepts, their relationships and patterns of behavior in terms of an ontology chart. Norm Analysis Method (NAM) is adopted to identify and formally specify patterns of behavior and rules that govern the actions identified on the ontology chart. Information collected during semantic and norm analysis is integrated to guide the generation of CPs using best practice represented in BPMN thus enabling the automation of CP. Findings: This research confirms the necessity of taking into consideration social aspects in designing information systems and automating CP. The complexity of healthcare processes can be best tackled by analyzing stakeholders, which we treat as social agents, their goals and patterns of action within the agent network. Originality/value: The current modeling methods describe CPs from a structural aspect comprising activities, properties and interrelationships. However, these methods lack a mechanism to describe possible patterns of human behavior and the conditions under which the behavior will occur. To overcome this weakness, a semiotic approach to generation of clinical pathway is introduced. The CP generated from SAM together with norms will enrich the knowledge representation of the domain through ontology modeling, which allows the recognition of human responsibilities and obligations and more importantly, the ultimate power of decision making in exceptional circumstances.

Extending the human nervous system through Internet implants - Experimentation and impact

It is now possible to directly link the human nervous system to a computer and thence onto the Internet. From an electronic and mental viewpoint this means that the Internet becomes an extension of the human nervous system (and vice versa). Such a connection on a regular or mass basis will have far reaching effects for society. In this article the authors discuss their own practical implant self-experimentation, especially insofar as it relates to extending the human nervous system. Trials involving an intercontinental link up are described. As well as technical aspects of the work, social, moral and ethical issues, as perceived by the authors, are weighed against potential technical gains. The authors also look at technical limitations inherent in the co-evolution of Internet implanted individuals as well as the future distribution of intelligence between human and machine.

This is me: digital identity and reputation on the Internet

The chapter reports on the ‘This Is Me’ project, that aimed to help students and the wider public to be aware of the impact that online material, particularly that on the Internet, has on their identity and reputation. The chapter explores practical aspects of Digital Identity, relating to issues such as employability, relationships and even death. For example, understanding the impact a photograph posted on a social networking website might have for different groups of people, ranging from friends or parents to future employers. As part of the ‘This is Me’ project stories were collected from students and others about Digital Identity matters, a grounded methodological approach based on action research was used to establish issues related to Digital Identity particularly relevant to those in academia. Drawing from these issues, resources were developed to help inform and educate people about how they can understand and control their own Digital Identity. A number of these resources are presented here, along with reflections on how they are used and can be adapted.

A survey of data mining techniques for social media analysis

Social network has gained remarkable attention in the last decade. Accessing social network sites such as Twitter, Facebook LinkedIn and Google+ through the internet and the web 2.0 technologies has become more affordable. People are becoming more interested in and relying on social network for information, news and opinion of other users on diverse subject matters. The heavy reliance on social network sites causes them to generate massive data characterised by three computational issues namely; size, noise and dynamism. These issues often make social network data very complex to analyse manually, resulting in the pertinent use of computational means of analysing them. Data mining provides a wide range of techniques for detecting useful knowledge from massive datasets like trends, patterns and rules [44]. Data mining techniques are used for information retrieval, statistical modelling and machine learning. These techniques employ data pre-processing, data analysis, and data interpretation processes in the course of data analysis. This survey discusses different data mining techniques used in mining diverse aspects of the social network over decades going from the historical techniques to the up-to-date models, including our novel technique named TRCM. All the techniques covered in this survey are listed in the Table.1 including the tools employed as well as names of their authors.

Self-concept clarity, social support, and Compulsive Internet Use: a study of the USA and the UAE

Compulsive Internet Use (CIU) has been mostly studied among adolescents, yet some studies reveal that this can be a problem for the adult population, too. The lack of agreement on diagnostic tools and cut-off points results in markedly different prevalence figures. Building on Charlton’s (2002) distinction between core CIU and positive engagement dimensions, the first objective was to confirm that prevalence figures including the core dimensions of CIU were lower than those including the engagement dimensions as well. Second, building on Davis’s (2001) diathesis-stress model, we tested the role that self-concept clarity (SCC) and social support play in predicting core CIU in US subjects (NUS = 268). Finally, we expected that, because self-concept clarity is mostly linked to well-being in Western countries, the association between this variable and core CIU would be weak in the Eastern culture sample (NUAE = 270). Our findings confirmed that prevalence figures were 20–40% lower when including the core dimensions only, and that SCC is a key predictor of CIU at low levels of social support in the US. We also confirmed that this is not the case in the UAE. Future research opportunities to advance this study were discussed.