Demo Data from SIGIR 2026 / reviewers in the wild / expert
Colleen Berryessa
dblp:367/7342 · also Colleen M. Berryessa
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2024
0000-0003-1670-7484ORCID · reported
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1 · 1 since 2021
Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.
| Network and information security
1 paper |
Security and privacy of machine learning · 62% Privacy and data protection · 38% | |
| Interdisciplinary, comprehensive, and emerging computing
1 paper |
Computational social science and digital humanities · 100% |
Topics — the 2 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Privacy and data protection › image privacy
image-based sexual abuse |
0.2 | 1 | 2024 | Non-Consensual Synthetic Intimate Imagery: Prevalence, Attitudes, and Knowledge in 10 Countries · CHI 2024 |
Privacy and data protection › image privacy
non-consensual intimate imagery |
0.2 | 1 | 2024 | Non-Consensual Synthetic Intimate Imagery: Prevalence, Attitudes, and Knowledge in 10 Countries · CHI 2024 |
Methods — techniques the papers use, named apart from their topics
survey · 1.5
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2024 | Non-Consensual Synthetic Intimate Imagery: Prevalence, Attitudes, and Knowledge in 10 CountriesabstractDeepfake technologies have become ubiquitous, “democratizing” the ability to manipulate photos and videos. One popular use of deepfake technology is the creation of sexually explicit content, which can then be posted and shared widely on the internet. Drawing on a survey of over 16,000 respondents in 10 different countries, this article examines attitudes and behaviors related to “deepfake pornography” as a specific form of non-consensual synthetic intimate imagery (NSII). Our study found that deepfake pornography behaviors were considered harmful by respondents, despite nascent societal awareness. Regarding the prevalence of deepfake pornography victimization and perpetration, 2.2% of all respondents indicated personal victimization, and 1.8% all of respondents indicated perpetration behaviors. Respondents from countries with specific legislation still reported perpetration and victimization experiences, suggesting NSII laws are inadequate to deter perpetration. Approaches to prevent and reduce harms may include digital literacy education, as well as enforced platform policies, practices, and tools which better detect, prevent, and respond to NSII content. Rebecca Umbach, Nicola Henry, Gemma Beard, Colleen Berryessa |
CHI | 4 |