1,881 research outputs found

    A case for contrast as a catalyst for change

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    This is a qualitative, largely reflective, interpretive case study of our evolution from teachers of market research to educational collaborators who work with students to co-develop qualitative researchers. This case both explores the ways to extend and improve qualitative research and researchers and presents a more general, interpretivist approach to problem-solving. The case is mixed method. It reports the combination and interpretation of reflective elements including articulating our individual memories and inter-relating these in a series of discussions where we also considered the nature and meaning of our educational approaches and the effectiveness of what we are doing

    Why happy shoppers don't stop and think

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    This paper discusses findings from observational research of grocery shopping. Videographic analysis via qualitative research techniques reveals that consumers who display less emotion tend to be more positive about the experience and have shorter shopping visits. Whereas those who display distinct emotional responses tend to reveal negative reactions and result in taking longer to make a decision. Four categories of consumer decision behaviour for grocery products are suggested as a result of this research and as a discussion point for further investigations into this specific topic

    Decremental All-Pairs ALL Shortest Paths and Betweenness Centrality

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    We consider the all pairs all shortest paths (APASP) problem, which maintains the shortest path dag rooted at every vertex in a directed graph G=(V,E) with positive edge weights. For this problem we present a decremental algorithm (that supports the deletion of a vertex, or weight increases on edges incident to a vertex). Our algorithm runs in amortized O(\vstar^2 \cdot \log n) time per update, where n=|V|, and \vstar bounds the number of edges that lie on shortest paths through any given vertex. Our APASP algorithm can be used for the decremental computation of betweenness centrality (BC), a graph parameter that is widely used in the analysis of large complex networks. No nontrivial decremental algorithm for either problem was known prior to our work. Our method is a generalization of the decremental algorithm of Demetrescu and Italiano [DI04] for unique shortest paths, and for graphs with \vstar =O(n), we match the bound in [DI04]. Thus for graphs with a constant number of shortest paths between any pair of vertices, our algorithm maintains APASP and BC scores in amortized time O(n^2 \log n) under decremental updates, regardless of the number of edges in the graph.Comment: An extended abstract of this paper will appear in Proc. ISAAC 201

    The nature and role of social relationships in social responsibility

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    The importance of socially responsible purchasing continues to grow. However there is limited work that considers high involvement purchasing and the importance of social relationships in building attitudes and guiding behavior in this context. This paper presents findings that consider these issues. Social relationships are found to be an important factor in responsible purchasing however these effects often are not consciously recognized by consumers. The paper concludes by considering the need for research methods to uncover the importance of social relations

    The Parameterized Complexity of Centrality Improvement in Networks

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    The centrality of a vertex v in a network intuitively captures how important v is for communication in the network. The task of improving the centrality of a vertex has many applications, as a higher centrality often implies a larger impact on the network or less transportation or administration cost. In this work we study the parameterized complexity of the NP-complete problems Closeness Improvement and Betweenness Improvement in which we ask to improve a given vertex' closeness or betweenness centrality by a given amount through adding a given number of edges to the network. Herein, the closeness of a vertex v sums the multiplicative inverses of distances of other vertices to v and the betweenness sums for each pair of vertices the fraction of shortest paths going through v. Unfortunately, for the natural parameter "number of edges to add" we obtain hardness results, even in rather restricted cases. On the positive side, we also give an island of tractability for the parameter measuring the vertex deletion distance to cluster graphs

    Graphitization of small carbonate samples for paleoceanographic research at the godwin radiocarbon laboratory, University of Cambridge

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    AbstractA new radiocarbon preparation facility was set up in 2010 at the Godwin Laboratory for Palaeoclimate Research, at the University of Cambridge. Samples are graphitized via hydrogen reduction on an iron powder catalyst before being sent to the Chrono Centre, Belfast, or the Australian National University for accelerator mass spectrometry (AMS) analysis. The experimental setup and procedure have recently been developed to investigate the potential for running small samples of foraminiferal carbonate. By analyzing background values of samples ranging from 0.04 to 0.6 mg C along with similar sized secondary standards, the setup and experimental procedures were optimized for small samples. “Background” modern 14C contamination has been minimized through careful selection of iron powder, and graphitization has been optimized through the use of “small volume” reactors, allowing samples containing as little as 0.08 mg C to be graphitized and accurately dated. Graphitization efficiency/fractionation is found not to be the main limitation on the analysis of samples smaller than 0.07 mg C, which rather depends primarily on AMS ion beam optics, suggesting further improvements in small sample analysis might yet be achieved with our methodology.We would like to thank James Rolfe for running the stable isotope measurements, as well as the Royal Society and NERC grant NE/L006421/1 for research support.This is the author accepted manuscript. The final version is available from Cambridge University Press via http://dx.doi.org/10.1017/RDC.2015.

    In times of need are there more reasons to be green?

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    There is concern that consumers may have turned their backs on Ethical and Socially Responsible (E&SR) products in response to the Global Financial Crisis (GFC). This paper reviews secondary data on consumers changes in E&SR purchasing as a result of the GFC, comparing it to the discourse of ten focus groups conducted immediately before and during the downturn. Our findings show that there has been little behaviour change in response to the downturn; E&SR products are perceived as more costly, consumer purchase decisions are primarily driven by cost rather than E&SR concerns, and consumers continue to purchase E&SR products that provide financial value

    Cycle-centrality in complex networks

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    Networks are versatile representations of the interactions between entities in complex systems. Cycles on such networks represent feedback processes which play a central role in system dynamics. In this work, we introduce a measure of the importance of any individual cycle, as the fraction of the total information flow of the network passing through the cycle. This measure is computationally cheap, numerically well-conditioned, induces a centrality measure on arbitrary subgraphs and reduces to the eigenvector centrality on vertices. We demonstrate that this measure accurately reflects the impact of events on strategic ensembles of economic sectors, notably in the US economy. As a second example, we show that in the protein-interaction network of the plant Arabidopsis thaliana, a model based on cycle-centrality better accounts for pathogen activity than the state-of-art one. This translates into pathogen-targeted-proteins being concentrated in a small number of triads with high cycle-centrality. Algorithms for computing the centrality of cycles and subgraphs are available for download

    Graph-based Features for Automatic Online Abuse Detection

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    While online communities have become increasingly important over the years, the moderation of user-generated content is still performed mostly manually. Automating this task is an important step in reducing the financial cost associated with moderation, but the majority of automated approaches strictly based on message content are highly vulnerable to intentional obfuscation. In this paper, we discuss methods for extracting conversational networks based on raw multi-participant chat logs, and we study the contribution of graph features to a classification system that aims to determine if a given message is abusive. The conversational graph-based system yields unexpectedly high performance , with results comparable to those previously obtained with a content-based approach
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