Name
Abstract | ||
|---|---|---|
A biological understanding is key for managing medical conditions, yet psychological and social aspects matter too. The main problem is that these two aspects are hard to
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">quantify</i>
and inherently difficult to
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">communicate</i>
. To
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">quantify</i>
psychological aspects, this work mined around half a million Reddit posts in the sub-communities specialised in 14 medical conditions, and it did so with a new deep-learning framework. In so doing, it was able to associate mentions of medical conditions with those of emotions. To then
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">quantify</i>
social aspects, this work designed a probabilistic approach that mines open prescription data from the National Health Service in England to compute the prevalence of drug prescriptions, and to relate such a prevalence to census data. To finally
<italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">visually communicate</i>
each medical condition's biological, psychological, and social aspects through storytelling, we designed a narrative-style layered Martini Glass visualization. In a user study involving 52 participants, after interacting with our visualization, a considerable number of them changed their mind on previously held opinions: 10% gave more importance to the psychological aspects of medical conditions, and 27% were more favourable to the use of social media data in healthcare, suggesting the importance of persuasive elements in interactive visualizations. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/TVCG.2020.3030391 | IEEE Transactions on Visualization and Computer Graphics |
Keywords | DocType | Volume |
Artificial Intelligence,Communication,Computer Graphics,Humans,Social Media,State Medicine | Journal | 27 |
Issue | ISSN | Citations |
2 | 1077-2626 | 0 |
PageRank | References | Authors |
0.34 | 17 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Wonyoung So | 1 | 0 | 0.68 |
| Edyta P. Bogucka | 2 | 2 | 1.46 |
| Sanja Šćepanović | 3 | 0 | 0.34 |
| Sagar Prakash Joglekar | 4 | 12 | 8.19 |
| Ke Zhou | 5 | 790 | 40.82 |
| Daniele Quercia | 6 | 1618 | 103.55 |