Research

Peer-Reviewed Publications

Urman A., Makhortykh M., Ulloa R. (2022) Auditing the representation of migrants in image web search results. Humanities and Social Sciences Communications. https://doi.org/10.1057/s41599-022-01144-1

de León, E., Makhortykh, M., Gil-Lopez, T., Urman, A., Adam, S. (2022). News, Threats, and Trust: How COVID-19 News Shaped Political Trust, and How Threat Perceptions Conditioned This Relationship. The International Journal of Press/Politics. https://doi.org/10.1177%2F19401612221087179

Makhortykh, M., Urman A., Münch, F., Heldt, A., Dreyer, S., & Kettemann, M. (2022). Not all who are bots are evil: A cross-platform analysis of automated agent governance. New Media and Society. https://doi.org/10.1177%2F14614448221079035

Boeker, M., & Urman, A. (Accepted, Forthcoming). An Empirical Investigation of Personalization Factors on TikTok. Proceedings of the Web Conference 2022. Preprint available at https://arxiv.org/abs/2201.12271

Makhortykh, M., Urman A., Wijermars, M. (2022) How search engines disseminate information about COVID-19 and why they should do better. The Harvard Kennedy School Misinformation Review. https://doi.org/10.37016/mr-2020-94

Urman, A., Ionescu, S., Garcia, D., & Hannák, A. (2022). The politicization of medical preprints on Twitter during the early stages of COVID-19 pandemic. Journal of Quantitative Description: Digital Media. https://doi.org/10.51685/jqd.2022.003

Makhortykh, M., Urman, A., Gil-Lopez, T., & Ulloa, R. (2021) To track or not to track: examining perceptions of online tracking for information behavior research. Internet Research. https://doi.org/10.1108/INTR-01-2021-0074

Urman, A., Ho, J. C., & Katz, S. (2021). Analyzing protest mobilization on Telegram: The case of 2019 Anti-Extradition Bill movement in Hong Kong. PLOS ONE, 16(10), e0256675. https://doi.org/10.1371/journal.pone.0256675

Makhortykh, M., Urman, A., & Ulloa, R. (2021) Hey, Google, is it what the Holocaust looked like? Auditing algorithmic curation of visual historical content on Web search engines. First Monday. https://doi.org/10.5210/fm.v26i10.11562

Urman A., Makhortykh M., Ulloa R. (2021) The Matter of Chance: Auditing Web Search Results Related to the 2020 U. S. Presidential Primary Elections Across Six Search Engines. Social Science Computer Review. https://doi.org/10.1177/08944393211006863

Makhortykh, M., Urman, A., & Ulloa, R. (2021) Detecting Race and Gender Bias in Visual Representation of AI on Web Search Engines. In L. Boratto, S. Faralli, M. Marras, & G. Stilo (Eds.), Advances in Bias and Fairness in Information Retrieval (pp. 36–50). Springer International Publishing. https://doi.org/10.1007/978-3-030-78818-6_5

Urman, A., Makhortykh, M., & Ulloa, R. (2021). Auditing Source Diversity Bias in Video Search Results Using Virtual Agents. Companion Proceedings of the Web Conference 2021, 232–236. https://doi.org/10.1145/3442442.3452306

Christner, C., Urman, A., Adam, S., & Maier, M. (2021). Automated Tracking Approaches for Studying Online Media Use: A Critical Review and Recommendations. Communication Methods and Measures, 0(0), 1–17. https://doi.org/10.1080/19312458.2021.1907841

Urman, A., & Makhortykh, M. (2021). There can be only one truth: Ideological segregation and online news communities in Ukraine. Global Media and Communication. https://doi.org/10.1177/17427665211009930

Urman, A., & Katz, S. (2020). What they do in the shadows: Examining the far-right networks on Telegram. Information, Communication & Society, 0(0), 1–20. https://doi.org/10.1080/1369118X.2020.1803946

Makhortykh, M., Urman, A., Ulloa, R. (2020) How search engines disseminate information about COVID-19 and why they should do better. The Harvard Kennedy School Misinformation Review. https://doi.org/10.37016/mr-2020-017

Urman, A. (2020). Context matters: political polarization on Twitter from a comparative perspective. Media, Culture & Societyhttps://doi.org/10.1177/0163443719876541

Urman, A. (2019). News Consumption of Russian Vkontakte Users: Polarization and News Avoidance. International Journal Of Communication, 13, 25. Retrieved from https://ijoc.org/index.php/ijoc/article/view/11161

Preprints

Sipka A., Hannak A. & Urman A. (2021). Comparing the Language of QAnon-related content on Parler, Gab, and Twitter [Preprint]. arXiv https://arxiv.org/abs/2111.11118

Urman, A., Makhortykh, M., Ulloa, R., & Kulshrestha, J. (2021) Where the Earth is flat and 9/11 is an inside job: A comparative algorithm audit of conspiratorial information in web search results [Preprint]. arXiv https://arxiv.org/abs/2112.01278

Ulloa, R., Makhortykh, M., & Urman, A. (2021) Algorithm Auditing at a Large-Scale: Insights from Search Engine Audits [Preprint].arXiv https://arxiv.org/abs/2106.05831

Urman, A., & Makhortykh, M. (2021) You Are How (and Where) You Search? Comparative Analysis of Web Search Behaviour Using Web Tracking Data [Preprint]. arXiv https://arxiv.org/abs/2105.04961

Urman, A., Ho, J. C., & Katz, S. (2020). “No Central Stage”: Telegram-based activity during the 2019 protests in Hong Kong [Preprint]. SocArXiv. https://doi.org/10.31235/osf.io/ueds4

Urman, A., Ionescu, S., Garcia, D., & Hannák, A. (2020). COVID-19 and the politicisation of medical preprints on Twitter: Quantitative Analysis of Social Media Data [Preprint]. https://doi.org/10.2196/preprints.25169