Abstract: In the past five years, as “big data” research increasingly has been adopted and adapted in the social sciences, the question of multimodal analysis pays a larger role in approaches and perspectives of research methodology. The buzzword "big data" has provoked critiques by a number of social scientists (eg., boyd & Crawford 2011; Bruns & Burgess 2012; Burrell 2012; Baym 2013; Lazer, et al. 2014; Tufekci 2014) on the theories, methodologies, and analysis of large data sources, and yet a growing number of scholars are experimenting with new ways to think about applying traditional and established methods to a newer domain and scale of data. Past panels (e.g., ICA 2013’s “Downsizing Data: Analyzing Social Digital Traces” and ICA 2014’s “Data-Driven Data Research Using Data and Databases: A Practical Critique of Methods and Approaches in ‘Big Data’ Studies”) have examined the practice of large-scale data analysis in social media research. This panel extends those discussions to look at the complications of mixed-methods research in big data studies, specifically in cases when “holistic,” population-level data is available.
The International Communication Association (ICA) is an academic association for scholars interested in the study, teaching, and application of all aspects of human and mediated communication. ICA began more than 50 years ago as a small association of U.S. researchers and is now a truly international association with more than 4,500 members in 80 countries. Since 2003, ICA has been officially associated with the United Nations as a non-governmental association (NGO).
Speaker(s)
R. Stuart Geiger
Former BIDS Ethnographer Stuart Geiger is now a faculty member at the University of California, San Diego, jointly appointed in the Department of Communication and the Halıcıoğlu Data Science Institute. At BIDS, as an ethnographer of science and technology, he studied the infrastructures and institutions that support the production of knowledge. He launched the Best Practices in Data Science discussion group in 2019, having been one of the original members of the MSDSE Data Science Studies Working Group. Previously, his work on Wikipedia focused on the community of volunteer editors who produce and maintain an open encyclopedia. He also studied distributed scientific research networks and projects, including the Long-Term Ecological Research Network and the Open Science Grid. In Wikipedia and scientific research, he studied topics including newcomer socialization, community governance, specialization and professionalization, quality control and verification, cooperation and conflict, the roles of support staff and technicians, and diversity and inclusion. And, as these communities are made possible through software systems, he studied how the design of software tools and systems intersect with all of these issues. He received an undergraduate degree at UT Austin, and an MA in Communication, Culture, and Technology at Georgetown University, where he began empirically studying communities using qualitative and ethnographic methods. As part of receiving his PhD from the UC Berkeley School of Information, he worked with anthropologists, sociologists, psychologists, historians, organizational and management scholars, designers, and computer scientists.