Demo Data from SIGIR 2026 / reviewers in the wild / expert
Junai Cai
dblp:319/4177
· DBLP profile ↗
1ranked-venue papers
0as first author
1since 2021 · last 2022
—ORCID · none
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.
| Human-computer interaction and pervasive computing
1 paper |
Design research and methods · 44% Collaborative and social computing · 44% Ubiquitous computing and smart environments · 13% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Collaborative and social computing › collaborative design
co-creation |
0.6 | 1 | 2022 | Establishing Design Consensus toward Next-Generation Retail: Data-Enabled Design Exploration and Participatory Analysis · CHI 2022 |
Design research and methods › research through design
data-enabled design |
0.6 | 1 | 2022 | Establishing Design Consensus toward Next-Generation Retail: Data-Enabled Design Exploration and Participatory Analysis · CHI 2022 |
Methods — techniques the papers use, named apart from their topics
data visualization · 0.6co-creation workshop · 0.6case study · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Establishing Design Consensus toward Next-Generation Retail: Data-Enabled Design Exploration and Participatory AnalysisabstractIntegration of online and offline retail faces challenges in technology adoption, interaction style evolution and customer behavior shifts, while also being complicated by diverse perspectives from different stakeholders of consumers, retail staff, and retail business unit people. To explore how we can tackle the aforementioned challenges, this work applied the data-enabled design method and participatory data analysis to a case study, where 400 student consumers’ shopping behavior data was collected, cross-analyzed, and visualized in a campus chain store. We then invited 13 stakeholders to join a co-creation workshop for a further participatory data analysis. In the workshop, the different stakeholders came to a design consensuses which we summarized into a series of practical design recommendations for improving the current store. Finally, we generalized the case study process as a contextual-informed-aware model, which can contribute to professional design practice for the retail industry. Junai Cai, Kexin Du, Yuxuan Hou, Haipeng Mi |
CHI | 2 |