Demo Data from EDBT 2026 / reviewers in the wild / expert
Lindsay Shaw Taylor
dblp:87/4135
· DBLP profile ↗
3ranked-venue papers
1as first author
0since 2021 · last 2014
—ORCID · none
Domains — the database's venue-derived domains; a paper can count in several
Human-computer interaction and ubiquitous computing · 3 · 1 first-authorDatabases, data management, data science and information retrieval · 1 · 1 first-authorApplied, interdisciplinary, general and emerging computing · 1 · 1 first-author
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 |
Ubiquitous computing and smart environments · 75% Collaborative and social computing · 25% | |
| Databases, data mining, and information retrieval
1 paper |
Web and social media mining · 100% |
Topics — the 3 heaviest of 4, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Ubiquitous computing and smart environments
incentive mechanism |
0.2 | 1 | 2014 | Incentives to participate in online research: an experimental examination of "surprise" incentives · CHI 2014 |
Collaborative and social computing › interpersonal relationships
online dating |
0.1 | 1 | 2008 | Assessing attractiveness in online dating profiles · CHI 2008 |
Ubiquitous computing and smart environments › mobile crowdsourcing › crowdsensing › mobile crowdsensing
user recruitment |
0.1 | 1 | 2014 | Incentives to participate in online research: an experimental examination of "surprise" incentives · CHI 2014 |
Methods — techniques the papers use, named apart from their topics
crowding theory · 0.2controlled experiment · 0.2user ratings study · 0.2
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2014 | Incentives to participate in online research: an experimental examination of "surprise" incentivesabstractThe recruitment of participants for online survey research presents many challenges. In this work, we present four experiments examining how two different kinds of "surprise" financial incentives affect the rate of participation in a longitudinal study when participants are initially solicited with either an appeal to intrinsic motivation to participate in research or one that also offers extrinsic financial incentives. We find that unexpected financial incentives ("existence surprises") presented to people who click a recruitment advertisement focused on intrinsic incentives lead to a lower recruitment rate than do the same incentives offered to those who clicked an advertisement that led them to expect it. However, when potential participants expect a financial incentive, surprising them with a higher amount ("amount surprises") yields a higher recruitment rate. We interpret these results in the context of crowding theory. Neither type of surprise affected ongoing participation, measured as the number of questions and questionnaires completed over the course of the study. Andrew T. Fiore, Coye Cheshire, Lindsay Shaw Taylor, G. A. Mendelsohn |
CHI | 3 |
| 2010 | A Second Chance to Make a First Impression: Factors Affecting the Longevity of Online Dating Relationships
Lindsay Shaw Taylor, Andrew T. Fiore, G. A. Mendelsohn, Coye Cheshire |
ICWSM | 1 |
| 2008 | Assessing attractiveness in online dating profilesabstractOnline dating systems play a prominent role in the social lives of millions of their users, but little research has considered how users perceive one another through their personal profiles. We examined how users perceive attractiveness in online dating profiles, which provide their first exposure to a potential partner. Participants rated whole profiles and profile components on such qualities as how attractive, extraverted, and genuine and trustworthy they appeared. As past research in the psychology of attraction would suggest, the attractiveness and other qualities of the photograph were the strongest predictors of whole profile attractiveness, but they were not alone: the free-text component also played an important role in predicting overall attractiveness. In turn, numerous other qualities predicted the attractiveness ratings of photos and free-text components, albeit in different ways for men and women. The fixed-choice elements of a profile, however, were unrelated to attractiveness. Author Keywords Online personals, attraction, computer-mediated Andrew T. Fiore, Lindsay Shaw Taylor, G. A. Mendelsohn, Marti A. Hearst |
CHI | 2 |