[Air-L] Seeking research interview participants
Sara.Mannheimer at montana.edu
Wed Jun 9 08:50:52 PDT 2021
Dear AoIR Community,
I am a librarian at Montana State University and a doctoral candidate at Humboldt University in Berlin (HU Supervisor: Vivien Petras; External Supervisor: Michael Zimmer, Marquette University).
I am conducting a research study that aims to understand how different research communities address data curation and data sharing. The results of the research will improve library and data repository practices. (Full summary of the research below this email.)
My request to this community:
I am looking for interview participants who use computational social science to analyze big social data such as social media, online forums, and blogs.
If you are willing to join me for a 60-75 minute interview, please contact me off-list at sara.mannheimer at montana.edu<mailto:%20sara.mannheimer at montana.edu>.
Thank you very much for considering!
Sara Mannheimer (she/her)
Associate Professor, Data Librarian - Montana State University
Doctoral Candidate - Humboldt University of Berlin
Full research summary
Big social data (such as social media and blogs) and archived qualitative data (such as interview transcripts, field notebooks, and diaries) are similar, but their respective communities of practice are under-connected. Research with both types of data repurpose existing social data to advance discoveries in social science. However, despite these similarities, big social research has not yet been widely framed as a form of qualitative data reuse, and qualitative data reuse has only begun to be discussed through a big social data lens. Qualitative data reuse is a more established practice, and therefore has more developed data curation strategies to support data sharing. My research investigates how data curation practices from each of these communities can inform the other for mutual benefit. The research will use interviews of qualitative researchers, big social data researchers, and data curators to gain insights into different community approaches to research and data sharing.
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