228,138 research outputs found

    Social Influence and the Collective Dynamics of Opinion Formation

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    Social influence is the process by which individuals adapt their opinion, revise their beliefs, or change their behavior as a result of social interactions with other people. In our strongly interconnected society, social influence plays a prominent role in many self-organized phenomena such as herding in cultural markets, the spread of ideas and innovations, and the amplification of fears during epidemics. Yet, the mechanisms of opinion formation remain poorly understood, and existing physics-based models lack systematic empirical validation. Here, we report two controlled experiments showing how participants answering factual questions revise their initial judgments after being exposed to the opinion and confidence level of others. Based on the observation of 59 experimental subjects exposed to peer-opinion for 15 different items, we draw an influence map that describes the strength of peer influence during interactions. A simple process model derived from our observations demonstrates how opinions in a group of interacting people can converge or split over repeated interactions. In particular, we identify two major attractors of opinion: (i) the expert effect, induced by the presence of a highly confident individual in the group, and (ii) the majority effect, caused by the presence of a critical mass of laypeople sharing similar opinions. Additional simulations reveal the existence of a tipping point at which one attractor will dominate over the other, driving collective opinion in a given direction. These findings have implications for understanding the mechanisms of public opinion formation and managing conflicting situations in which self-confident and better informed minorities challenge the views of a large uninformed majority.Comment: Published Nov 05, 2013. Open access at: http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.007843

    Mapping the information-coping trajectory of young people coping with long term illness: An evidence based approach

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    Purpose - Purpose: We explore the relationship between information and coping information from the experiences of young people coping with long term illness. Design/methodology/approach - Methodology: Situational Analysis was used as a methodological approach. It has roots in the Chicago Symbolic Interactionism School. Cartographic approaches enabled the analysis, mapping the complexities emerging from the data. Findings - Findings: As the young people became more informed about their health conditions, and gained knowledge and understanding both about their illnesses, their own bodies and boundaries, their confidence and capacity to cope increased. Gaining confidence, the young people often wanted to share their knowledge becoming information providers themselves. From the data we identified five positions on an information-coping trajectory (1) Information deficiency (2) Feeling ill-informed (3) Needing an injection of information (4) Having information health and (5) Becoming an information donor. Research limitations/implications - Research limitations/implications: The research was limited to an analysis of thirty narratives. The research contributes to information theory by mapping clearly the relationship between information and coping. Originality/value - Originality/value: The information theories in this study have originality and multi-disciplinary value in the management of health and illness, and information studies

    Poor Philanthropist III: A Practice-relevant Guide for Community Philanthropy

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    This is a guide for a research study carried out between 2003 and 2005, the purpose of which was to explore the local ethos of caring and sharing in poor African communities.This guide is intended to assist grantmakers and funders working with impoverished communities in applying a PoC lens to their practice

    Poor Philanthropist III: A Practice Relevant Guide to Community Philanthropy

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    This guide has its origins in a research study carried out between 2003 and 2005, the purpose of which was to explore the local ethos of caring and sharing in poor African communities. Focus groups carried out by national research teams in Namibia, Mozambique, South Africa and Zimbabwe generated rich narrative text revealing what the term 'help' means to the poor, who helps and is helped in poor communities, the forms help takes and, finally, why people help each other. This knowledge informed the first systematic understanding of 'indigenous philanthropy' in southern Africa. To emphasise the local ethos of caring and sharing and make it more visible to development organisations, it was named. The term 'horizontal philanthropy' or 'philanthropy of community' (PoC) was coined and the research findings documented in a 2005 monograph entitled, The Poor Philanthropist: How and Why the Poor Help Each Other (Wilkinson-Maposa, Fowler, Oliver-Evans & Mulenga 2005). The findings published in 2005 sparked the interest of the development community

    Explore, Exploit or Listen: Combining Human Feedback and Policy Model to Speed up Deep Reinforcement Learning in 3D Worlds

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    We describe a method to use discrete human feedback to enhance the performance of deep learning agents in virtual three-dimensional environments by extending deep-reinforcement learning to model the confidence and consistency of human feedback. This enables deep reinforcement learning algorithms to determine the most appropriate time to listen to the human feedback, exploit the current policy model, or explore the agent's environment. Managing the trade-off between these three strategies allows DRL agents to be robust to inconsistent or intermittent human feedback. Through experimentation using a synthetic oracle, we show that our technique improves the training speed and overall performance of deep reinforcement learning in navigating three-dimensional environments using Minecraft. We further show that our technique is robust to highly innacurate human feedback and can also operate when no human feedback is given
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