Name
Abstract | ||
|---|---|---|
The study and analysis of large and complex data sets offer a wealth of insights in a variety of applications. Computational approaches provide researchers access to broad assemblages of data, but the insights extracted may lack the rich detail that qualitative approaches have brought to the understanding of sociotechnical phenomena. How do we preserve the richness associated with traditional qualitative methods while utilizing the power of large data sets? How do we uncover social nuances or consider ethics and values in data use? These and other questions are explored by human-centered data science, an emerging field at the intersection of human-computer interaction (HCI), computer-supported cooperative work (CSCW), human computation, and the statistical and computational techniques of data science. This workshop, the first of its kind at CSCW, seeks to bring together researchers interested in human-centered approaches to data science to collaborate, define a research agenda, and form a community. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1145/2818052.2855518 | CSCW Companion |
Keywords | Field | DocType |
Data Science, Human-Centered Design, Human-Centered Data Science, Research Methods, Social Media | Data science,Data set,Computer-supported cooperative work,Computer science,Cooperative work,Knowledge management,Complex data type,Human–computer interaction,Sociotechnical system,Qualitative research,Management science,User-centered design,Social media | Conference |
Citations | PageRank | References |
2 | 0.38 | 6 |
Authors | ||
9 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Cecilia R. Aragon | 1 | 1165 | 223.72 |
| C.J. Hutto | 2 | 264 | 10.00 |
| Andy Echenique | 3 | 28 | 3.66 |
| Brittany Fiore-Gartland | 4 | 3 | 1.06 |
| Yun Huang | 5 | 92 | 12.01 |
| Jinyoung Kim | 6 | 54 | 3.25 |
| Gina Neff | 7 | 3 | 3.11 |
| Wanli Xing | 8 | 64 | 8.28 |
| Joseph B. Bayer | 9 | 23 | 1.99 |