Adam Bradley

adam_portrait

Adam Bradley, BA (McMaster) MA (Waterloo), is a PhD student interested in the intersections between technology and traditional literary studies. His MA research project, titled "Data Visualization and the Avant-Garde Aesthetic" was a digital humanities project completed in conjunction with the English department?s Digital Media Lab and the Computer Science department?s Touchlab. His project investigated whether shifting the aesthetics of a given text can offer new insights into the study of its structure and how the integrity of that text can be maintained within this paradigm. Other interests include ancient rhetoric, classical languages, and modernist literature.

  • Email: adam [dot] bradley [at] uwaterloo [dot] ca

Projects

Publications

2016

  • A. J. Bradley, T. Kirton, M. Hancock, and S. Carpendale, Language DNA: Visualizing a language decomposition, Digital Humanities Quarterly, vol. 10, iss. 4, 2016.

    In the Digital Humanities, there is a fast-growing body of research that uses data visualization to explore the structures of language. While new techniques are proliferating they still fall short of offering whole language experimentation. We provide a mathematical technique that maps words and symbols to ordered unique numerical values, showing that this mapping is one-to-one and onto. We demonstrate this technique through linear, planar, and volumetric visualizations of data sets as large as the Oxford English Dictionary and as small as a single poem. The visualizations of this space have been designed to engage the viewer in the analogic practice of comparison already in use by literary critics but on a scale inaccessible by other means. We studied our visualization with expert participants from many fields including English studies, Information Visualization, Human-Computer Interaction, and Computer Graphics. We present our findings from this study and discuss both the criticisms and validations of our approach.

    @article{Bradley:2016:LDNA, author = {Adam James Bradley and Travis Kirton and Mark Hancock and Sheelagh Carpendale}, title = {Language {DNA}: Visualizing a language decomposition}, journal = {Digital Humanities Quarterly}, issue_date = {2016}, volume = {10}, number = {4}, year = {2016}, issn = {1938-4122}, publisher = {ADHO}, abstract = {In the Digital Humanities, there is a fast-growing body of research that uses data visualization to explore the structures of language. While new techniques are proliferating they still fall short of offering whole language experimentation. We provide a mathematical technique that maps words and symbols to ordered unique numerical values, showing that this mapping is one-to-one and onto. We demonstrate this technique through linear, planar, and volumetric visualizations of data sets as large as the Oxford English Dictionary and as small as a single poem. The visualizations of this space have been designed to engage the viewer in the analogic practice of comparison already in use by literary critics but on a scale inaccessible by other means. We studied our visualization with expert participants from many fields including English studies, Information Visualization, Human-Computer Interaction, and Computer Graphics. We present our findings from this study and discuss both the criticisms and validations of our approach.}, url = {http://www.digitalhumanities.org/dhq/vol/10/4/000259/000259.html}, subtype = {journal} }

2015

  • A. Bradley, C. MacArthur, M. Hancock, and S. Carpendale, Gendered or Neutral? Considering the Language of HCI, in Proc. GI, Toronto, Ont., Canada, Canada, 2015, pp. 163-170.

    In this paper, we present a Mechanical Turk study that explores how the most common words that have been used to refer to people in recent HCI literature are received by non-experts. The top five CHI 2014 people words are: user, participant, person, designer, and researcher. We asked participants to think about one of these words for ten seconds and then to draw an image of it. After the drawing was done we asked simple demographic questions about both the participant and the created image. Our results show that while generally our participants did perceive most of these words as predominately male, there were two notable exceptions. Women appear to perceive the terms "person" and "participant" as gender neutral. That is, they were just as likely to draw a person or a participant as male or female. So while these two words are not exactly gender neutral in that men largely perceived them as male, at least women did not appear to feel excluded by these terms. We offer an increased understanding of the perception of HCIs people words and discuss the challenges this poses to our community in striving toward gender inclusiveness.

    @inproceedings{Bradley:2015:Users,
    author = {Adam Bradley and Cayley MacArthur and Mark Hancock and Sheelagh Carpendale},
    title = {Gendered or Neutral? Considering the Language of {HCI}},
    booktitle = {Proc. GI},
    series = {GI '15},
    year = {2015},
    location = {Halifax, Nova Scotia, Canada},
    pages = {163--170},
    publisher = {Canadian Information Processing Society},
    address = {Toronto, Ont., Canada, Canada},
    abstract={In this paper, we present a Mechanical Turk study that explores how the most common words that have been used to refer to people in recent HCI literature are received by non-experts. The top five CHI 2014 people words are: user, participant, person, designer, and researcher. We asked participants to think about one of these words for ten seconds and then to draw an image of it. After the drawing was done we asked simple demographic questions about both the participant and the created image. Our results show that while generally our participants did perceive most of these words as predominately male, there were two notable exceptions. Women appear to perceive the terms "person" and "participant" as gender neutral. That is, they were just as likely to draw a person or a participant as male or female. So while these two words are not exactly gender neutral in that men largely perceived them as male, at least women did not appear to feel excluded by these terms. We offer an increased understanding of the perception of HCIs people words and discuss the challenges this poses to our community in striving toward gender inclusiveness.},
    pdf={gi2015-gendered-language.pdf},
    subtype={conference}
    }

Adam Bradley
UW Touchlab