**Project description:**
This project contains all materials (except for the Twitter/X Data which cannot be shared for legal reasons according to thw X/Twitter Terms of Service) necessary to reproduce the results of Knöpfle & Schatto-Eckrodt (2024).
The folder "Empirical Claims Protocol" contains the protocol of all reproduced claims in Schatto-Eckrodt et al. (2024).
The folder "Replication Code" contains all code necessary to perform the replication ("Replication Code/Scripts") and all output including the re-trained topic models and figures ("Replication Code/Output").
The folder "Reproduction Code" contains all code necessary to perform the reproduction ("Reproduction Code/Scripts") and all output including the reproduced topic models and figures of Schatto-Eckrodt et al. (2020) ("Reproduction Code/Output").
The folder "Software environment" contains code and instructions on how to reproduce the initial computational environment of Schatto-Eckrodt et al. (2020) as well as the computational environment of Knöpfle and Schatto-Eckrodt (2024).
**Data collection instructions:**
To re-collect the data please use the tweet IDs (provided in the Excel and CSV-file format) in the "Tweet IDs" project folder and use the R-code in the "Twitter Data Collection Code" folder. We used the "Basic API" model of Twitter (Status: Feb. 2024) for two months to re-collect the data of Schatto-Eckrodt et al. (2020).
*Citations:*
Knöpfle, P. & Schatto-Eckrodt. T. (2024). The challenges of replicating volatile platform-data studies: A replication case study of Schatto-Eckrodt et al. (2020). Media and Communication.
Schatto-Eckrodt, T., Janzik, R., Reer, F., Boberg, S., & Quandt, T. (2020). A computational approach to analyzing the Twitter debate on gaming disorder. Media and Communication, 8(3), 205-218.
