Demo Data from EDBT 2026 / reviewers in the wild / expert
Seung Wan Ha
dblp:374/8794
· DBLP profile ↗
2ranked-venue papers
1as first author
2since 2021 · last 2025
0000-0002-4853-8550ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 2 · 1 first-author · 2 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.
| Human-computer interaction and pervasive computing
2 papers |
Design research and methods · 54% Health and well-being technologies · 46% | |
| Software engineering, system software, and programming languages
1 paper |
Empirical software engineering · 100% | |
| Network and information security
1 paper |
Usable security · 100% |
Topics — the 1 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Empirical software engineering
qualitative research |
0.8 | 1 | 2024 | Understanding fraudulence in online qualitative studies: From the researcher's perspective · CHI 2024 |
Methods — techniques the papers use, named apart from their topics
interview study · 2.3qualitative study · 0.9
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2025 | Preparing and Experiencing Food During Life Events: Implications for Technology Supporting Social and Value ChangesabstractPeer Reviewed Seung Wan Ha, Novia Nurain, Elena Agapie, Chia-Fang Chung |
CHI | 1 |
| 2024 | Understanding fraudulence in online qualitative studies: From the researcher's perspectiveabstractResearchers are increasingly facilitating qualitative research studies online. While this has made research more accessible for participation, there have been notable encounters with “fraudulent” participants. By fraudulent, we refer to individuals who are deceptive about meeting the inclusion criteria, their identity, or experiences. Fraudulent participants have generated new challenges for researchers who have to interact 1:1 with these individuals, face ethical dilemmas on appropriate next steps, diagnose and prevent the issue from happening again, and deal with their own identity as a scholar. In this study, we interview 16 HCI researchers to understand and learn from their experiences. We contribute: (1) an understanding of how HCI qualitative researchers deal with fraudulent participants; (2) a guide for qualitative HCI researchers on how to handle fraudulence; and (3) a reflection on how the HCI research community might better improve our science and training efforts. Aswati Panicker, Novia Nurain, Zaidat Ibrahim, Chun-Han Ariel Wang, Seung Wan Ha, Yuxing Wu, Kay Connelly, Katie A. Siek, Chia-Fang Chung |
CHI | 5 |