13,842 research outputs found

    Quantifying and minimizing risk of conflict in social networks

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    Controversy, disagreement, conflict, polarization and opinion divergence in social networks have been the subject of much recent research. In particular, researchers have addressed the question of how such concepts can be quantified given people’s prior opinions, and how they can be optimized by influencing the opinion of a small number of people or by editing the network’s connectivity. Here, rather than optimizing such concepts given a specific set of prior opinions, we study whether they can be optimized in the average case and in the worst case over all sets of prior opinions. In particular, we derive the worst-case and average-case conflict risk of networks, and we propose algorithms for optimizing these. For some measures of conflict, these are non-convex optimization problems with many local minima. We provide a theoretical and empirical analysis of the nature of some of these local minima, and show how they are related to existing organizational structures. Empirical results show how a small number of edits quickly decreases its conflict risk, both average-case and worst-case. Furthermore, it shows that minimizing average-case conflict risk often does not reduce worst-case conflict risk. Minimizing worst-case conflict risk on the other hand, while computationally more challenging, is generally effective at minimizing both worst-case as well as average-case conflict risk

    On green routing and scheduling problem

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    The vehicle routing and scheduling problem has been studied with much interest within the last four decades. In this paper, some of the existing literature dealing with routing and scheduling problems with environmental issues is reviewed, and a description is provided of the problems that have been investigated and how they are treated using combinatorial optimization tools

    The normalized Friedkin-Johnsen model (a work-in-progress report)

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    The formation of opinions in a social context has long been studied by sociologists. A well-known model is due to Friedkin and Johnsen (further referenced as the FJ model), which assumes that individuals hold an immutable internal opinion while they express an opinion that may differ from it but is more in agreement with the expressed opinions of their friends. Formally, the expressed opinion is modeled as the weighted average of the individual's internal opinion and the expressed opinions of their neighbors. This model has been used in recent research originating from the computer science community, studying the origination and reduction of conflict on social networks, how echo chambers arise and can be burst, and more. Yet, we argue that the FJ model in its elementary form is not suitable for some of these purposes. Indeed, the FJ model entails that the more friends one has, the less one's internal opinion matters in the formation of one's expressed opinion. Arguing that this may not be realistic, we propose a modification of the FJ model that normalizes the influence of one's friends and keeps the influence of one's internal opinion constant. This normalization was in fact suggested by Friedkin and Johnsen, but it has been ignored in much of the recent computer science literature. In this work-in-progress report, we present the details of the normalized model, and investigate the consequences of this normalization, both theoretically and empirically

    Oceans and the Sustainable Development Goals: Co-Benefits, Climate Change & Social Equity

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    Achieving ocean sustainability is paramount for coastal communities and marine industries, yet is also inextricably linked to much broader global sustainable development—including increased resilience to climate change and improved social equity—as envisioned by the UN 2030 Agenda for Sustainable Development. This report highlights the co-benefits from achieving each SDG 14 target: progress towards each of the other 161 SDG targets when ocean targets are met, given ten-year lag times between ocean targets and other SDG targets. The identification of co-benefits is based on input from more than 30 scientific experts in the Nereus Program. Below we highlight notable co-benefits of achieving each target within SDG 14

    Personality cannot be predicted from the power of resting state EEG

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    In the present study we asked whether it is possible to decode personality traits from resting state EEG data. EEG was recorded from a large sample of subjects (N = 309) who had answered questionnaires measuring personality trait scores of the 5 dimensions as well as the 10 subordinate aspects of the Big Five. Machine learning algorithms were used to build a classifier to predict each personality trait from power spectra of the resting state EEG data. The results indicate that the five dimensions as well as their subordinate aspects could not be predicted from the resting state EEG data. Finally, to demonstrate that this result is not due to systematic algorithmic or implementation mistakes the same methods were used to successfully classify whether the subject had eyes open or eyes closed and whether the subject was male or female. These results indicate that the extraction of personality traits from the power spectra of resting state EEG is extremely noisy, if possible at all.Comment: 14 pages, 4 figure

    Spatial optimization for land use allocation: accounting for sustainability concerns

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    Land-use allocation has long been an important area of research in regional science. Land-use patterns are fundamental to the functions of the biosphere, creating interactions that have substantial impacts on the environment. The spatial arrangement of land uses therefore has implications for activity and travel within a region. Balancing development, economic growth, social interaction, and the protection of the natural environment is at the heart of long-term sustainability. Since land-use patterns are spatially explicit in nature, planning and management necessarily must integrate geographical information system and spatial optimization in meaningful ways if efficiency goals and objectives are to be achieved. This article reviews spatial optimization approaches that have been relied upon to support land-use planning. Characteristics of sustainable land use, particularly compactness, contiguity, and compatibility, are discussed and how spatial optimization techniques have addressed these characteristics are detailed. In particular, objectives and constraints in spatial optimization approaches are examined
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