205,772 research outputs found

    From the User to the Medium: Neural Profiling Across Web Communities

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    Online communities provide a unique way for individuals to access information from those in similar circumstances, which can be critical for health conditions that require daily and personalized management. As these groups and topics often arise organically, identifying the types of topics discussed is necessary to understand their needs. As well, these communities and people in them can be quite diverse, and existing community detection methods have not been extended towards evaluating these heterogeneities. This has been limited as community detection methodologies have not focused on community detection based on semantic relations between textual features of the user-generated content. Thus here we develop an approach, NeuroCom, that optimally finds dense groups of users as communities in a latent space inferred by neural representation of published contents of users. By embedding of words and messages, we show that NeuroCom demonstrates improved clustering and identifies more nuanced discussion topics in contrast to other common unsupervised learning approaches

    Mind the gap? The persistence of pathological discourses in urban regeneration policy

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    Urban regeneration policy has historically framed policy problems using a discourse that pathologises areas and spatial communities. Since 2001 in England, and 2002 in Scotland a structural change in policy has occurred where citywide partnerships are now meant overcome structural spatial inequalities, countering pathological explanations. This paper uses historical and discourse analysis to evaluate one of the major community regeneration strategies developed by the Scottish Executive in 2002: Better Communities in Scotland: Closing the Gap. It seeks to ask whether structural change in policy was paralleled by discursive change; what discursive path dependence is evidenced? The text is placed in the historic context of UK urban renewal policies dating back to the launch of the Urban Programme in 1968 and particularly the policy discourse created by the influential Conservative government policy of 1988 New Life for Urban Scotland and the wider discourses of poverty and neighbourhood renewal policy created by Labour governments since 1997. The close textual analysis of the text shows that Better Communities in Scotland continues to pathologise spatial communities. Although this suggests a degree of historical path dependency, the historic breadth of the analysis also problematises simple historical determinism

    Crossing Selma\u27s Bridge: Integrating Visual Discovery Strategy and Young Adult Literature to Promote Dialogue and Understanding

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    Urban communities, separated by race and class, experience a disproportionate number of gun deaths, police shootings, crime, violent and nonviolent protests, as well as disparities in housing, education, and employment. These discussions are visual and textual, appearing in both traditional and social media outlets. How do adolescents read and make sense of these images? We discuss integrating a Social Studies practice, Visual Discovery Strategy, with Young Adult Literature to provide students with the skills to both critique images from the events in their lives and produce responses through both traditional and digital methods

    Logic Against Bias: Textual Entailment Mitigates Stereotypical Sentence Reasoning

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    Due to their similarity-based learning objectives, pretrained sentence encoders often internalize stereotypical assumptions that reflect the social biases that exist within their training corpora. In this paper, we describe several kinds of stereotypes concerning different communities that are present in popular sentence representation models, including pretrained next sentence prediction and contrastive sentence representation models. We compare such models to textual entailment models that learn language logic for a variety of downstream language understanding tasks. By comparing strong pretrained models based on text similarity with textual entailment learning, we conclude that the explicit logic learning with textual entailment can significantly reduce bias and improve the recognition of social communities, without an explicit de-biasing processComment: Accepted by EACL 202

    Textual Materialities, Agents of Exchange and Translational Communities

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    A review ofAnne E.B. Coldiron. Printers without Borders. Translation and Textuality in the Renaissance. Cambridge University Press, 2015. William T. Rossiter. Wyatt Abroad. Tudor Diplomacy and the Translation of Power. Cambridge, UK: D.S. Brewer, 2014.

    Structures in Crisis: A Narrative Approach to Asghar Farhadi’s Films

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    This paper proposes an exploration of the films of Iranian director Asghar Farhadi. It employs a methodology based on textual analysis, focusing specifically on the structural design of his films and the focalization processes of his scripts. It shows how Farhadi’s work can be understood as a coherent research project with a uniquely solid model based on chronological linearity as a way to explore the violent breakdown of different emotional communities: families, marriages, groups of friends, etc. At the same time, it considers how all the focalization processes in his films are oriented toward two main concepts: knowledge (of the characters, but also of the audience) and pain (of living in a [narrative] world afflicted by meaninglessness)
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