A new Handbook of Computational Social Science has just been published in two volumes:

U. Engel, A. Quan-Haase, S. Xun Liu, & L.E. Lyberg (2022). Handbook of Computational Social Science. Volume 1 Theory, Case Studies and Ethics. Routledge. ISBN 9780367456528 https://www.routledge.com/Handbook-of-Computational-Social-Science-Volume-1-Theory-Case-Studies/Engel-Quan-Haase-Liu-Lyberg/p/book/9780367456528

U. Engel, A. Quan-Haase, S. Xun Liu, & L.E. Lyberg (2022). Handbook of Computational Social Science. Volume 2 Data Science, Statistical Modelling, and Machine Learning Methods. Routledge. ISBN 9781032077703 https://www.routledge.com/Handbook-of-Computational-Social-Science-Volume-2-Data-Science-Statistical/Engel-Quan-Haase-Liu-Lyberg/p/book/9781032077703

The second volume includes the following chapter:
Indira Sen, Fabian Flöck, Katrin Weller, Bernd Weiß and Claudia Wagner: Applying a Total Error Framework for Digital Traces to Social Media Research. 

In this chapter, the authors use different application scenarios to explain how their Total Error Framework for Digital Traces of Human Behavior on Online Platforms (TED-On) can be applied to research scenarios that are based on data collected from Online Platforms (such as social media) in order to identify potential pitfalls and limitations in the research design.