CHIIR 2023 paper about how gender is and should be used in information retrieval research and practice, with an eye towards promoting inclusiveness and gender equity.
CHIIR 2023 paper about how gender is and should be used in information retrieval research and practice, with an eye towards promoting inclusiveness and gender equity.
CHIIR 2023 paper about how gender is and should be used in information retrieval research and practice, with an eye towards promoting inclusiveness and gender equity.
Friends, I am thrilled to share our recent #CHIIR2023 paper where we examined how data scientists seek, read, and understand research papers!
Paper: https://arxiv.org/abs/2301.03774
(sacrilegious) Tweet thread: https://twitter.com/MSheshera/status/1613388613126963203
Our paper grounds our findings in a number of interesting (and sometimes underappreciated!) prior and ongoing work, and speculates on meaningful future work in IR, NLP, HCI, and CSCW! I hope you read our paper and get in touch if you'd like to chat!
Keeping up with the research literature plays an important role in the workflow of scientists - allowing them to understand a field, formulate the problems they focus on, and develop the solutions that they contribute, which in turn shape the nature of the discipline. In this paper, we examine the literature review practices of data scientists. Data science represents a field seeing an exponential rise in papers, and increasingly drawing on and being applied in numerous diverse disciplines. Recent efforts have seen the development of several tools intended to help data scientists cope with a deluge of research and coordinated efforts to develop AI tools intended to uncover the research frontier. Despite these trends indicative of the information overload faced by data scientists, no prior work has examined the specific practices and challenges faced by these scientists in an interdisciplinary field with evolving scholarly norms. In this paper, we close this gap through a set of semi-structured interviews and think-aloud protocols of industry and academic data scientists (N = 20). Our results while corroborating other knowledge workers' practices uncover several novel findings: individuals (1) are challenged in seeking and sensemaking of papers beyond their disciplinary bubbles, (2) struggle to understand papers in the face of missing details and mathematical content, (3) grapple with the deluge by leveraging the knowledge context in code, blogs, and talks, and (4) lean on their peers online and in-person. Furthermore, we outline future directions likely to help data scientists cope with the burgeoning research literature.
CHIIR 2023 paper about how gender is and should be used in information retrieval research and practice, with an eye towards promoting inclusiveness and gender equity.
Michael Ekstrand
Sheshera Mysore