Demo Data from SIGIR 2026 / reviewers in the wild / expert
Weston L. Baxter
dblp:287/7476
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 1
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 |
Human-AI interaction · 50% Usability and user experience research · 50% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-AI interaction
conversational agents |
0.4 | 1 | 2019 | Understanding Affective Experiences with Conversational Agents · CHI 2019 |
Usability and user experience research › user affect
emotional experience |
0.4 | 1 | 2019 | Understanding Affective Experiences with Conversational Agents · CHI 2019 |
Methods — techniques the papers use, named apart from their topics
survey study · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Understanding Affective Experiences with Conversational AgentsabstractWhile previous studies of Conversational Agents (e.g. Siri, Google Assistant, Alexa and Cortana) have focused on evaluating usability and exploring capabilities of these systems, little work has examined users' affective experiences. In this paper we present a survey study with 171 participants to examine CA users' affective experiences. Specifically, we present four major usage scenarios, users' affective responses in these scenarios, and the factors which influenced the affective responses. We found that users' overall experience was positive with interest being the most salient positive emotion. Affective responses differed depending on the scenarios. Both pragmatic and hedonic qualities influenced affect. The factors underlying pragmatic quality are: helpfulness, proactivity, fluidity, seamlessness and responsiveness. The factors underlying hedonic quality are: comfort in human-machine conversation, pride of using cutting-edge technology, fun during use, perception of having a human-like assistant, concern about privacy and fear of causing distraction. Xi Yang 0010, Marco Aurisicchio, Weston L. Baxter |
CHI | 3 |