108 citations · 261 across the 14 of their papers we have counts for
15 papers
Googling the Big Lie: Search Engines, News Media, and the US 2020 Election Conspiracy
Ernesto de León, Mykola Makhortykh, Aleksandra Urman +1
The conspiracy theory that the US 2020 presidential election was fraudulent - the Big Lie - remained a prominent part of the media agenda months after the election. Whether and how…
Improving the quality of individual-level online information tracking: challenges of existing approaches and introduction of a new content- and long-tail sensitive academic solution
Silke Adam, Mykola Makhortykh, Michaela Maier +6
This article evaluates the quality of data collection in individual-level desktop information tracking used in the social sciences and shows that the existing approaches face sampl…
Algorithmically Curated Lies: How Search Engines Handle Misinformation about US Biolabs in Ukraine
Elizaveta Kuznetsova, Mykola Makhortykh, Maryna Sydorova +3
The growing volume of online content prompts the need for adopting algorithmic systems of information curation. These systems range from web search engines to recommender systems a…
In Generative AI we Trust: Can Chatbots Effectively Verify Political Information?
Elizaveta Kuznetsova, Mykola Makhortykh, Victoria Vziatysheva +3
This article presents a comparative analysis of the ability of two large language model (LLM)-based chatbots, ChatGPT and Bing Chat, recently rebranded to Microsoft Copilot, to det…
The right to audit and power asymmetries in algorithm auditing
Aleksandra Urman, Ivan Smirnov, Jana Lasser
In this paper, we engage with and expand on the keynote talk about the Right to Audit given by Prof. Christian Sandvig at the IC2S2 2021 through a critical reflection on power asym…
Novelty in news search: a longitudinal study of the 2020 US elections
Roberto Ulloa, Mykola Makhortykh, Aleksandra Urman +1
The 2020 US elections news coverage was extensive, with new pieces of information generated rapidly. This evolving scenario presented an opportunity to study the performance of sea…
This is what a pandemic looks like: Visual framing of COVID-19 on search engines
Mykola Makhortykh, Aleksandra Urman, Roberto Ulloa
In today's high-choice media environment, search engines play an integral role in informing individuals and societies about the latest events. The importance of search algorithms i…
Panning for gold: Lessons learned from the platform-agnostic automated detection of political content in textual data
Mykola Makhortykh, Ernesto de León, Aleksandra Urman +5
The growing availability of data about online information behaviour enables new possibilities for political communication research. However, the volume and variety of these data ma…
An Empirical Investigation of Personalization Factors on TikTok
Maximilian Boeker, Aleksandra Urman
TikTok currently is the fastest growing social media platform with over 1 billion active monthly users of which the majority is from generation Z. Arguably, its most important succ…
Where the Earth is flat and 9/11 is an inside job: A comparative algorithm audit of conspiratorial information in web search results
Aleksandra Urman, Mykola Makhortykh, Roberto Ulloa +1
Web search engines are important online information intermediaries that are frequently used and highly trusted by the public despite multiple evidence of their outputs being subjec…
Comparing the Language of QAnon-related content on Parler, Gab, and Twitter
Andrea Sipka, Aniko Hannak, Aleksandra Urman
Parler, a "free speech" platform popular with conservatives, was taken offline in January 2021 due to the lack of moderation of hateful and QAnon- and other conspiracy-related cont…
Detecting race and gender bias in visual representation of AI on web search engines
Mykola Makhortykh, Aleksandra Urman, Roberto Ulloa
Web search engines influence perception of social reality by filtering and ranking information. However, their outputs are often subjected to bias that can lead to skewed represent…
Auditing Source Diversity Bias in Video Search Results Using Virtual Agents
Aleksandra Urman, Mykola Makhortykh, Roberto Ulloa
We audit the presence of domain-level source diversity bias in video search results. Using a virtual agent-based approach, we compare outputs of four Western and one non-Western se…
You Are How (and Where) You Search? Comparative Analysis of Web Search Behaviour Using Web Tracking Data
Aleksandra Urman, Mykola Makhortykh
We conduct a comparative analysis of desktop web search behaviour of users from Germany (n=558) and Switzerland (n=563) based on a combination of web tracking and survey data. We f…
The Matter of Chance: Auditing Web Search Results Related to the 2020 U.S. Presidential Primary Elections Across Six Search Engines
Aleksandra Urman, Mykola Makhortykh, Roberto Ulloa
We examine how six search engines filter and rank information in relation to the queries on the U.S. 2020 presidential primary elections under the default - that is nonpersonalized…