Dear colleagues,

Please consider submitting an abstract to the Sunbelt 2024 organized session "Big data and field research in the study of social networks".  Please find further information below.

link to conference webpage: https://sunbelt2024.com/

For any questions, please feel free to contact me or Nikolitsa!

We look forward to meeting you in Edinburgh! All best, Betina

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*Big data and field research in the study of social networks*

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One of the major promises of “big data” was the ability to understand how social networks emerge, operate, and shape human behavior on a much larger scale than previously possible. Researchers have used large-scale network data to generate new insights on topics as varied as network evolution (Kossinets and Watts 2006), well-being (Jaidka et al. 2020), and political misinformation (Guess, Nyhan, and Reifler 2020), among many others. But researchers have become increasingly cognizant of the limits of “big data” analyses, which may include sampling bias in the data, confounds in the algorithms needed to uncover patterns, and weak construct validity (boyd and Crawford 2012; Lazer et al. 2014). An important response has been to address the limits of the data themselves by employing mixed- or multi-methods approaches that capitalize on the strengths of traditional social science methods, such as surveys, experiments, or various qualitative methods (Bail et al. 2020; Gilbert and Karahalios 2009; Grigoropoulou and Small 2022; Scharkow et al. 2020).

This organized session aims to host paper presentations on research in social networks that combine different types of data and methods. Critical reviews discussing specific methodological problems in large-scale network data and how they can be addressed with field research are also welcome.

*Organizers:*Nikolitsa Grigoropoulou, University of Bremen, grigorop@uni-bremen.de Betina Hollstein, University of Bremen, betina.hollstein@uni-bremen.de