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Hide and Seek in Slovakia: Utilizing Tracking Code Data to Uncover Untrustworthy Website Networks

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Disinformation in Open Online Media (MISDOOM 2021)

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 12887))

Abstract

The proliferation of misleading or false information spread by untrustworthy websites has emerged as a significant concern on the public agenda in many countries, including Slovakia. Despite the influence ascribed to such websites, their transparency and accountability remain an issue in most cases, with published work on mapping the administrators and connections of untrustworthy websites remaining limited. This article contributes to this body of knowledge (i) by providing an effective open-source tool to uncover untrustworthy website networks based on the utilization of the same Google Analytics/AdSense IDs, with the added ability to expose networks based on historical data, and (ii) by providing insight into the Slovak untrustworthy website landscape through delivering a first of its kind mapping of Slovak untrustworthy website networks. Our approach is based on a mix-method design employing a qualitative exploration of data collected in a two-wave study conducted in 2019 and 2021, utilizing a custom-coded tool to uncover website connections. Overall, the study succeeds in exposing multiple novel website ties. Our findings indicate that while some untrustworthy website networks have been found to operate in the Slovak infosphere, most researched websites appear to be run by multiple mutually unconnected administrators. The resulting data also demonstrates that untrustworthy Slovak websites display a high content diversity in terms of connected websites, ranging from websites of local NGOs, an e-shop selling underwear to a matchmaking portal.

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Contributions

J.M.M. designed the study; M.K. coded the python script with input from J.M.M.; K.F. supervised the research and provided funding; J.M.M. collected the data and analyzed the data with input from K.F.; J.M.M. wrote the paper with input from K.F. All authors reviewed the results and approved the final version of the manuscript.

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Funding

This work was supported by IBM (IBM Faculty Award 2017), VEGA (grant project n. 1/0433/18) and APVV (grant project n. APVV-20-0334). The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Author information

Authors and Affiliations

  1. Department of Security Studies and UMB Data & Society Lab at CEKR, Matej Bel University, Banská Bystrica, Slovakia

    Jozef Michal Mintal & Karol Fabián

  2. Center for Media, Data and Society at CEU Democracy Institute, Central European University, Budapest, Hungary

    Jozef Michal Mintal

  3. Morione, Bratislava, Slovakia

    Michal Kalman

Authors
  1. Jozef Michal Mintal
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  2. Michal Kalman
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  3. Karol Fabián
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Corresponding author

Correspondence to Jozef Michal Mintal .

Editor information

Editors and Affiliations

  1. University of Oxford, Oxford, UK

    Jonathan Bright

  2. Utrecht University, Utrecht, The Netherlands

    Anastasia Giachanou

  3. University of Leeds, Leeds, UK

    Viktoria Spaiser

  4. Boise State University, Boise, ID, USA

    Francesca Spezzano

  5. University of Oxford, Oxford, UK

    Anna George

  6. University of Oxford, Oxford, UK

    Alexandra Pavliuc

Ethics declarations

The code is available via GitHub at https://doi.org/10.5281/zenodo.4783300; the code is published under a GNU General Public License. The data that support the findings of this study have been deposited in Zenodo at https://doi.org/10.5281/zenodo.4783287; the data are available upon reasonable request.

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Mintal, J.M., Kalman, M., Fabián, K. (2021). Hide and Seek in Slovakia: Utilizing Tracking Code Data to Uncover Untrustworthy Website Networks. In: Bright, J., Giachanou, A., Spaiser, V., Spezzano, F., George, A., Pavliuc, A. (eds) Disinformation in Open Online Media. MISDOOM 2021. Lecture Notes in Computer Science(), vol 12887. Springer, Cham. https://doi.org/10.1007/978-3-030-87031-7_7

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  • DOI: https://doi.org/10.1007/978-3-030-87031-7_7

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-87030-0

  • Online ISBN: 978-3-030-87031-7

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