Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem

D. Assenmacher, D. Weber, M. Preuss, A.C. Valdez, A. Bradshaw, B. Ross, S. Cresci, H. Trautmann, F. Neumann, C. Grimme, Social Science Computer Review 40 (2022) 1496–1522.

Download
No fulltext has been uploaded.
Journal Article | English
Author
Assenmacher, Dennis; Weber, Derek; Preuss, Mike; Valdez, André Calero; Bradshaw, Alison; Ross, Björn; Cresci, Stefano; Trautmann, HeikeLibreCat ; Neumann, Frank; Grimme, Christian
Abstract
Computational social science uses computational and statistical methods in order to evaluate social interaction. The public availability of data sets is thus a necessary precondition for reliable and replicable research. These data allow researchers to benchmark the computational methods they develop, test the generalizability of their findings, and build confidence in their results. When social media data are concerned, data sharing is often restricted for legal or privacy reasons, which makes the comparison of methods and the replicability of research results infeasible. Social media analytics research, consequently, faces an integrity crisis. How is it possible to create trust in computational or statistical analyses, when they cannot be validated by third parties? In this work, we explore this well-known, yet little discussed, problem for social media analytics. We investigate how this problem can be solved by looking at related computational research areas. Moreover, we propose and implement a prototype to address the problem in the form of a new evaluation framework that enables the comparison of algorithms without the need to exchange data directly, while maintaining flexibility for the algorithm design.
Publishing Year
Journal Title
Social Science Computer Review
Volume
40
Issue
6
Page
1496-1522
LibreCat-ID

Cite this

Assenmacher D, Weber D, Preuss M, et al. Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem. Social Science Computer Review. 2022;40(6):1496-1522. doi:10.1177/08944393211012268
Assenmacher, D., Weber, D., Preuss, M., Valdez, A. C., Bradshaw, A., Ross, B., Cresci, S., Trautmann, H., Neumann, F., & Grimme, C. (2022). Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem. Social Science Computer Review, 40(6), 1496–1522. https://doi.org/10.1177/08944393211012268
@article{Assenmacher_Weber_Preuss_Valdez_Bradshaw_Ross_Cresci_Trautmann_Neumann_Grimme_2022, title={Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem}, volume={40}, DOI={10.1177/08944393211012268}, number={6}, journal={Social Science Computer Review}, author={Assenmacher, Dennis and Weber, Derek and Preuss, Mike and Valdez, André Calero and Bradshaw, Alison and Ross, Björn and Cresci, Stefano and Trautmann, Heike and Neumann, Frank and Grimme, Christian}, year={2022}, pages={1496–1522} }
Assenmacher, Dennis, Derek Weber, Mike Preuss, André Calero Valdez, Alison Bradshaw, Björn Ross, Stefano Cresci, Heike Trautmann, Frank Neumann, and Christian Grimme. “Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem.” Social Science Computer Review 40, no. 6 (2022): 1496–1522. https://doi.org/10.1177/08944393211012268.
D. Assenmacher et al., “Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem,” Social Science Computer Review, vol. 40, no. 6, pp. 1496–1522, 2022, doi: 10.1177/08944393211012268.
Assenmacher, Dennis, et al. “Benchmarking Crisis in Social Media Analytics: A Solution for the Data-Sharing Problem.” Social Science Computer Review, vol. 40, no. 6, 2022, pp. 1496–522, doi:10.1177/08944393211012268.

Export

Marked Publications

Open Data LibreCat

Search this title in

Google Scholar