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Full-Text Articles in Arts and Humanities

A Pedagogy Of Techno-Social Relationality: Ethics And Digital Multimodality In The Composition Classroom, Kristin M. Ravel Aug 2019

A Pedagogy Of Techno-Social Relationality: Ethics And Digital Multimodality In The Composition Classroom, Kristin M. Ravel

Theses and Dissertations

I bring together the relational ethics of feminist critical theory with approaches of multimodal rhetoric to examine the ethical implications of composing on social media platforms. Most social media platforms are designed to value consumerism, efficiency, quantity of web traffic, and constant synchronous response over concerns of responsible and critical communication. I propose a rhetorical approach of techno-social relationality (TSR) as an intervention against such corporate-minded design. Through this approach, I argue that civil engagement is not limited to people’s social responsibilities but rather is entwined in complex, material-technical contexts. By considering the responsibility of our machines as much as …


The Use Of Deep Learning Distributed Representations In The Identification Of Abusive Text, Susan Mckeever, Hao Chen, Sarah Jane Delany Jan 2019

The Use Of Deep Learning Distributed Representations In The Identification Of Abusive Text, Susan Mckeever, Hao Chen, Sarah Jane Delany

Conference papers

The selection of optimal feature representations is a critical step in the use of machine learning in text classification. Traditional features (e.g. bag of words and n-grams) have dominated for decades, but in the past five years, the use of learned distributed representations has become increasingly common. In this paper, we summarise and present a categorisation of the stateof-the-art distributed representation techniques, including word and sentence embedding models. We carry out an empirical analysis of the performance of the various feature representations using the scenario of detecting abusive comments. We compare classification accuracies across a range of off-the-shelf embedding models …