Demo Data from SIGIR 2026 / reviewers in the wild / expert
Anushk Mittal
dblp:319/4042
· 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 |
Human-AI interaction · 50% Collaborative and social computing · 50% | |
| Artificial intelligence
1 paper |
Language models and text generation · 100% |
Topics — the 2 heaviest of 3, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Human-AI interaction
AI-mediated communication |
0.6 | 1 | 2022 | Will AI Console Me when I Lose my Pet? Understanding Perceptions of AI-Mediated Email Writing · CHI 2022 |
Collaborative and social computing › computer-mediated communication
interpersonal trust |
0.6 | 1 | 2022 | Will AI Console Me when I Lose my Pet? Understanding Perceptions of AI-Mediated Email Writing · CHI 2022 |
Methods — techniques the papers use, named apart from their topics
survey · 1.1interviews · 1.1
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Will AI Console Me when I Lose my Pet? Understanding Perceptions of AI-Mediated Email WritingabstractLarge language models are increasingly mediating, modifying, and even generating messages for users, but the receivers of these messages may not be aware of the involvement of AI. To examine this emerging direction of AI-Mediated Communication (AI-MC), we investigate people’s perceptions of AI written messages. We analyze how such perceptions change in accordance with the interpersonal emphasis of a given message. We conducted both large-scale surveys and in-depth interviews to investigate how a diverse set of factors influence people’s perceived trust in AI-mediated writing of emails. We found that people’s trust in email writers decreased when they were told that AI was involved in the writing process. Surprisingly trust increased when AI was used for writing more interpersonal emails (as opposed to more transactional ones). Our study provides insights regarding how people perceive AI-MC and has practical design implications on building AI-based products to aid human interlocutors in communication1. Anushk Mittal, Diyi Yang, Amy S. Bruckman |
CHI | 2 |