Group consensus in social influence:type of consensus information as a moderator of majority and minority influence

Three experiments investigated the effect of consensus information on majority and minority influence. Experiment 1 examined the effect of consensus expressed by descriptive adjectives (large vs. small) on social influence. A large source resulted in more influence than a small source, irrespective of source status (majority vs. minority). Experiment 2 showed that large sources affected attitudes heuristically, whereas only a small minority instigated systematic processing of the message. Experiment 3 manipulated the type of consensus information, either in terms of descriptive adjectives (large, small) or percentages (82%, 18%, 52%, 48%). When consensus was expressed in terms of descriptive adjectives, the findings of Experiments 1 and 2 were replicated (large sources were more influential than small sources), but when consensus was expressed in terms of percentages, the majority was more influential than the minority, irrespective of group consensus.

Robust automatic mapping algorithms in a network monitoring scenario

Automatically generating maps of a measured variable of interest can be problematic. In this work we focus on the monitoring network context where observations are collected and reported by a network of sensors, and are then transformed into interpolated maps for use in decision making. Using traditional geostatistical methods, estimating the covariance structure of data collected in an emergency situation can be difficult. Variogram determination, whether by method-of-moment estimators or by maximum likelihood, is very sensitive to extreme values. Even when a monitoring network is in a routine mode of operation, sensors can sporadically malfunction and report extreme values. If this extreme data destabilises the model, causing the covariance structure of the observed data to be incorrectly estimated, the generated maps will be of little value, and the uncertainty estimates in particular will be misleading. Marchant and Lark [2007] propose a REML estimator for the covariance, which is shown to work on small data sets with a manual selection of the damping parameter in the robust likelihood. We show how this can be extended to allow treatment of large data sets together with an automated approach to all parameter estimation. The projected process kriging framework of Ingram et al. [2007] is extended to allow the use of robust likelihood functions, including the two component Gaussian and the Huber function. We show how our algorithm is further refined to reduce the computational complexity while at the same time minimising any loss of information. To show the benefits of this method, we use data collected from radiation monitoring networks across Europe. We compare our results to those obtained from traditional kriging methodologies and include comparisons with Box-Cox transformations of the data. We discuss the issue of whether to treat or ignore extreme values, making the distinction between the robust methods which ignore outliers and transformation methods which treat them as part of the (transformed) process. Using a case study, based on an extreme radiological events over a large area, we show how radiation data collected from monitoring networks can be analysed automatically and then used to generate reliable maps to inform decision making. We show the limitations of the methods and discuss potential extensions to remedy these.

Non sexist-translation and/in social change: gender issues in translation

Following centuries of feminist struggle, centuries which have born witness to the close relationship between linguistic discrimination and social reality, there is a growing tendency in modern society to acknowledge the vital role played by language in overcoming gender discrimination. Political institutions are currently compensating by instituting the use of non-sexist language through legislative guidelines, and this makes an important contribution to social reform for equality between the sexes. Seeing that translation is so important for the creation of the collective identities on which modern global society depends, it is clear that non-sexist translation is crucial if there is to be non-sexist language. In this article I examine the potential of non-sexist translation in the struggle for gender equality from a both a theoretical and a practical viewpoint, and I end with a critical evaluation of non-sexist translation methods.

Accommodating special needs users in the evaluation of an m-Learning application:a case study

Adult illiteracy rates are alarmingly high worldwide. The portability, affordability, and ease of use of mobile (or handheld) devices offer a realistic opportunity to provide novel, context-sensitive literacy resources to adults with limited literacy skills. To this end, we developed the concept of ALEX – a mobile Adult Literacy support application for EXperiential learning (Lumsden et al., 2005). On the basis of a medium-fidelity prototype of this application, we conducted an evaluation of ALEX using participants from our in tended user group. This evaluation had two goals: (a) to assess the usefulness of the ALEX concept and the usability of its current design; and (b) to reflect on the appropriateness of our evaluation process given the literacy-related needs of our participants. This paper outlines our approach to this evaluation as well as the results we obtained and our reflections on the process.

About Problems of Decision Making in Social and Economic Systems

The reasons of a restricted applicability of the models of decision making in social and economic systems. 3 basic principles of growth of their adequacy are proposed: "localization" of solutions, direct account of influencing of the individual on process of decision making ("subjectivity of objectivity") and reduction of influencing of the individual psychosomatic characteristics of the subject (" objectivity of subjectivity ") are offered. The principles are illustrated on mathematical models of decision making in ecologically- economic and social systems.

Method of Finding Hamilton Routes in Transport Network

This article discusses a solution method for Hamilton Problem, which either finds the task's solution, or indicates that the task is unsolvable. Offered method has significantly smaller requirements for computing resources than known algorithms.

Harnessing linked knowledge sources for topic classification in social media

Topic classification (TC) of short text messages offers an effective and fast way to reveal events happening around the world ranging from those related to Disaster (e.g. Sandy hurricane) to those related to Violence (e.g. Egypt revolution). Previous approaches to TC have mostly focused on exploiting individual knowledge sources (KS) (e.g. DBpedia or Freebase) without considering the graph structures that surround concepts present in KSs when detecting the topics of Tweets. In this paper we introduce a novel approach for harnessing such graph structures from multiple linked KSs, by: (i) building a conceptual representation of the KSs, (ii) leveraging contextual information about concepts by exploiting semantic concept graphs, and (iii) providing a principled way for the combination of KSs. Experiments evaluating our TC classifier in the context of Violence detection (VD) and Emergency Responses (ER) show promising results that significantly outperform various baseline models including an approach using a single KS without linked data and an approach using only Tweets. Copyright 2013 ACM.

Performance evaluation of adaptive context aware rate selection algorithm (ACARS) for road safety applications in vehicular network

One of the major drawbacks for mobile nodes in wireless networks is power management. Our goal is to evaluate the performance power control scheme to be used to reduce network congestion, improve quality of service and collision avoidance in vehicular network and road safety application. Some of the importance of power control (PC) are improving spatial reuse, and increasing network capacity in mobile wireless communications. In this simulation we have evaluated the performance of existing rate algorithms compared with context Aware Rate selection algorithm (ACARS) and also seen the performance of ACARS and how it can be applied to road safety, improve network control and power management. Result shows that ACARS is able to minimize the total transmit power in the presence of propagation processes and mobility of vehicles, by adapting to the fast varying channels conditions with the Path loss exponent values that was used for that environment which is shown in the network simulation parameter. Our results have shown that ACARS is a very robust algorithm which performs very well with the effect of propagation processes that is prone to every transmitted signal in mobile networks. © 2013 IEEE.

Women’s Entrepreneurship: closing the gender gap in access to financial and other services and in social entrepreneurship

This study explores differences between men and women entrepreneurs and social entrepreneurs. It explores the barriers and discriminatory effects that hinder women’s entrepreneurship, including access to finance in the European Union. The study includes four case studies covering the situation in the Czech Republic, Italy, Sweden, and the United Kingdom.

Role of the educator in social software initiatives in Further and Higher Education:a conceptualisation and research agenda

Higher and further education institutions are increasingly using social software tools to support teaching and learning. A growing body of research investigates the diversity of tools and their range of contributions. However, little research has focused on investigating the role of the educator in the context of a social software initiative, even though the educator is critical for the introduction and successful use of social software in a course environment. Hence, we argue that research on social software should place greater emphasis on the educators, as their roles and activities (such as selecting the tools, developing the tasks and facilitating the student interactions on these tools) are instrumental to most aspects of a social software initiative. To this end, we have developed an agenda for future research on the role of the educator. Drawing on role theory, both as the basis for a systematic conceptualization of the educator role and as a guiding framework, we have developed a series of concrete research questions that address core issues associated with the educator roles in a social software context and provide recommendations for further investigations. By developing a research agenda we hope to stimulate research that creates a better understanding of the educator’s situation and develops guidelines to help educators carry out their social software initiatives. Considering the significant role an educator plays in the initiation and conduct of a social software initiative, our research agenda ultimately seeks to contribute to the adoption and efficient use of social software in the educational domain.

Human capital in social and commercial entrepreneurship

We advance research on human capital and entrepreneurial entry and posit that, in order to generate value, social entrepreneurship requires different configurations of human capital than commercial entrepreneurship. We develop a multilevel framework to analyse the commonalities and differences between social and commercial entrepreneurship, including the impact of general and specific human capital, of national context and its moderating effect on the human capital-entrepreneurship relationship. We find that specific entrepreneurial human capital is relatively more important in commercial entrepreneurship, and general human capital in social entrepreneurship, and that the effects of human capital depend on the rule of law.