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Dietmar Janetzko

Biographic Data

ID4987341
NAMEDietmar Janetzko
GIVEN NAMESDietmar
FAMILY NAMEJanetzko
SIGNATUREJANETZKO D
AFFILIATIONSCBS University of Applied Sciences
ORCID0000-0003-2123-8424
VERIFIEDYes
TOTAL WORKS2
TOTAL CITATIONS13
WORKS AS AUTHOR2
WORKS AS EDITOR0
FIRST PUBLICATION YEAR2016
LATEST PUBLICATION YEAR2021
H-INDEX1
  • Are Social Bots on Twitter Political Actors? Empirical Evidence from a Ukrainian Social Botnet

    Open Access•Simon Hegelich, Dietmar Janetzko•ARTICLE•Proceedings of the International…•2021•Cited by: 13

    A considerable amount of data in social networks like Twitter is not generated by humans but by automatic programs (bots). Some of these bots are mimicking humans (socialbots) and can hardly be identified. In this article, we analyze a social botnet involved in the Ukrainian/Russian conflict. Based on text mining and unsupervised learning, we can identify three different behaviors: mimicry, window dressing, and reverberation

  • The Role of APIs in Data Sampling from Social Media

    Dietmar Janetzko•CHAPTER•The Sage Handbook of Social Media…•2016

  • Are Social Bots on Twitter Political Actors? Empirical Evidence from a Ukrainian Social Botnet

    Open Access•Simon Hegelich, Dietmar Janetzko•ARTICLE•Proceedings of the International…•2021•Cited by: 13

    A considerable amount of data in social networks like Twitter is not generated by humans but by automatic programs (bots). Some of these bots are mimicking humans (socialbots) and can hardly be identified. In this article, we analyze a social botnet involved in the Ukrainian/Russian conflict. Based on text mining and unsupervised learning, we can identify three different behaviors: mimicry, window dressing, and reverberation

  • The Role of APIs in Data Sampling from Social Media

    Dietmar Janetzko•CHAPTER•The Sage Handbook of Social Media…•2016

  • Are Social Bots on Twitter Political Actors? Empirical Evidence from a Ukrainian Social Botnet

    Open Access•Simon Hegelich, Dietmar Janetzko•ARTICLE•Proceedings of the International…•2021•Cited by: 13

    A considerable amount of data in social networks like Twitter is not generated by humans but by automatic programs (bots). Some of these bots are mimicking humans (socialbots) and can hardly be identified. In this article, we analyze a social botnet involved in the Ukrainian/Russian conflict. Based on text mining and unsupervised learning, we can identify three different behaviors: mimicry, window dressing, and reverberation

Computer Science (2 works) · Data science (2 works) · Social media (2 works) · World Wide Web (2 works) · Biology (1 work) · Botnet (1 work) · Complex Network Analysis Techniques (1 work) · Computer vision (1 work) · Empirical evidence (1 work) · Internet privacy (1 work)

Ethnos_APP • Open Source Project • MIT License • Frontend v2.0.0 • Privacy and Cookies • API Documentation: api.ethnos.app/docs • API Source Code: GitHub • DOI: 10.5281/zenodo.17049435 • Frontend Source Code: GitHub • DOI: 10.5281/zenodo.17050053 • cruz.rio.br • Expectantes Misericordiae