Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies
if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the
same subfield and year (this is the minimum needed to enter the top 1%, not the average
within it), or reaches the top citation threshold in at least one of its specific research
topics.
Alexa, Are You Listening?
2018362 citationsFlorian Schaub et al.Proceedings of the ACM on Human-Computer Interactionprofile →
Nudges for Privacy and Security
2017317 citationsAlessandro Acquisti, Lorrie Faith Cranor et al.profile →
Countries citing papers authored by Florian Schaub
Since
Specialization
Citations
This map shows the geographic impact of Florian Schaub's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Florian Schaub with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Florian Schaub more than expected).
This network shows the impact of papers produced by Florian Schaub. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Florian Schaub. The network helps show where Florian Schaub may publish in the future.
Co-authorship network of co-authors of Florian Schaub
This figure shows the co-authorship network connecting the top 25 collaborators of Florian Schaub.
A scholar is included among the top collaborators of Florian Schaub based on the total number of
citations received by their joint publications. Widths of edges
represent the number of papers authors have co-authored together.
Node borders
signify the number of papers an author published with Florian Schaub. Florian Schaub is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
McDonald, Allison, et al.. (2021). "It's stressful having all these phones": Investigating Sex Workers' Safety Goals, Risks, and Practices Online. USENIX Security Symposium. 375–392.5 indexed citations
Mhaidli, Abraham, Yixin Zou, & Florian Schaub. (2019). "We Can't Live Without Them!" App Developers' Adoption of Ad Networks and Their Considerations of Consumer Risks.. Symposium On Usable Privacy and Security. 225–244.15 indexed citations
14.
Frik, Alisa, et al.. (2019). Privacy and Security Threat Models and Mitigation Strategies of Older Adults. Symposium On Usable Privacy and Security. 21–40.49 indexed citations
15.
Harkous, Hamza, Kassem Fawaz, Rémi Lebret, et al.. (2018). Polisis: Automated Analysis and Presentation of Privacy Policies Using Deep Learning. Infoscience (Ecole Polytechnique Fédérale de Lausanne). 531–548.19 indexed citations
16.
Zou, Yixin, et al.. (2018). I've got nothing to lose: consumers' risk perceptions and protective actions after the equifax data breach. Symposium On Usable Privacy and Security. 197–216.24 indexed citations
17.
Sathyendra, Kanthashree Mysore, Florian Schaub, Shomir Wilson, & Norman Sadeh. (2016). Automatic extraction of opt-out choices from privacy policies. National Conference on Artificial Intelligence. 270–275.14 indexed citations
18.
Schaub, Florian, et al.. (2016). Drone-based Privacy Interfaces: Opportunities and Challenges. Symposium On Usable Privacy and Security.8 indexed citations
19.
Gluck, Joshua, Florian Schaub, Amy L. Friedman, et al.. (2016). How Short Is Too Short? Implications of Length and Framing on the Effectiveness of Privacy Notices. Symposium On Usable Privacy and Security. 321–340.38 indexed citations
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive
bibliographic database. While OpenAlex provides broad and valuable coverage of the global
research landscape, it—like all bibliographic datasets—has inherent limitations. These include
incomplete records, variations in author disambiguation, differences in journal indexing, and
delays in data updates. As a result, some metrics and network relationships displayed in
Rankless may not fully capture the entirety of a scholar's output or impact.