One-day workshop to be held Sunday, January 5, 2020 at GROUP 2020 on Sanibel Island, FL.
Social media platforms and social network sites generate a multitude of digital trace behavioral data, the scale of which often necessitates the use of computational data science methods. On the other hand, the socio-behavioral and often relational nature of the social media data requires the attention to context of user activity traditionally associated with qualitative analysis. Human-Centered Data Science (HCDS) attempts to bridge this gap by both harnessing the power of computational techniques and accounting for highly situated and nuanced nature of the social media activity. In this workshop we plan to consider the methods, pitfalls, and approaches of how to do HCDS effectively. Moreover, from collating and organizing these approaches we hope to progress to considering best (or at least common) practices in HCDS.
- Bring together and establish a community of sociotechnical researchers from various disciplines and methodological traditions who are interested in combining the human-centered perspective with the computational power of data science methods
- Encourage interaction and collaboration between researchers from different domain areas and methodological traditions.
- Collate a list of existing practices in Human-Centered Data Science and approach the issue of the best practices in this domain.
- Organize the existing practices into coherent emergent categories that will help the HCDS community to refine and extend its practices.
- Compile a HCDS reading list, organized by the above categories, and enable further community engagement with this list through comments.