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Towards reproducibility in online social network research

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tetc2015.pdf (387Kb)
Date
03/2018
Author
Hutton, Luke
Henderson, Tristan
Keywords
Data sharing
Online social networks
Reproducibility
Survey
QA75 Electronic computers. Computer science
DAS
BDC
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Abstract
The challenge of conducting reproducible computational research is acknowledged across myriad disciplines from biology to computer science. In the latter, research leveraging online social networks (OSNs) must deal with a set of complex issues, such as ensuring data can be collected in an appropriate and reproducible manner. Making research reproducible is difficult, and researchers may need suitable incentives, and tools and systems, to do so. In this paper, we explore the state-of-the-art in OSN research reproducibility, and present an architecture to aid reproducibility. We characterize the reproducible OSN research using three main themes: 1) reporting of methods; 2) availability of code; and 3) sharing of research data. We survey 505 papers and assess the extent to which they achieve these reproducibility objectives. While systems-oriented papers are more likely to explain data-handling aspects of their methodology, social science papers are better at describing their participant-handling procedures. We then examine incentives to make research reproducible, by conducting a citation analysis of these papers. We find that sharing data are associated with increased citation count, while sharing method and code does not appear to be. Finally, we introduce our architecture which supports the conduct of reproducible OSN research, which we evaluate by replicating an existing research study.
Citation
Hutton , L & Henderson , T 2018 , ' Towards reproducibility in online social network research ' , IEEE Transactions on Emerging Topics in Computing , vol. 6 , no. 1 , pp. 156-167 . https://doi.org/10.1109/TETC.2015.2458574
Publication
IEEE Transactions on Emerging Topics in Computing
Status
Peer reviewed
DOI
https://doi.org/10.1109/TETC.2015.2458574
ISSN
2168-6750
Type
Journal article
Rights
© © 2015 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Description
This work was supported by the Engineering and Physical Sciences Research Council [grant number EP/J500549/1].
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  • University of St Andrews Research
URI
http://hdl.handle.net/10023/7210

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