Demo Data from SIGIR 2026 / reviewers in the wild / expert
Lauren L. Saling
dblp:65/757
· DBLP profile ↗
2ranked-venue papers
0as first author
1since 2021 · last 2022
0000-0003-0722-6232ORCID · corroborated
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1 · 1 since 2021Human-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.
| Databases, data mining, and information retrieval
1 paper |
Information retrieval · 100% | |
| Human-computer interaction and pervasive computing
1 paper |
Usability and user experience research · 100% |
Topics — the 4 heaviest of 5, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval
information seeking |
0.6 | 1 | 2022 | Where Do Queries Come From? · SIGIR 2022 |
Information retrieval
query formulation |
0.6 | 1 | 2022 | Where Do Queries Come From? · SIGIR 2022 |
Information retrieval › query understanding
query variation |
0.6 | 1 | 2022 | Where Do Queries Come From? · SIGIR 2022 |
Computational social science and digital humanities
online behavior |
0.0 | 1 | 2000 | Potential determinants of heavier internet usage · Int. J. Hum. Comput. Stud. 2000 |
Methods — techniques the papers use, named apart from their topics
small experiments · 0.6literature review · 0.6
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2022 | Where Do Queries Come From?abstractWhere do queries -- the words searchers type into a search box -- come from? The Information Retrieval community understands the performance of queries and search engines extensively, and has recently begun to examine the impact of query variation, showing that different queries for the same information need produce different results. In an information environment where bad actors try to nudge searchers toward misinformation, this is worrisome. The source of query variation -- searcher characteristics, contextual or linguistic prompts, cognitive biases, or even the influence of external parties -- while studied in a piecemeal fashion by other research communities has not been studied by ours. In this paper we draw on a variety of literatures (including information seeking, psychology, and misinformation), and report some small experiments to describe what is known about where queries come from, and demonstrate a clear literature gap around the source of query variations in IR. We chart a way forward for IR to research, document and understand this important question, with a view to creating search engines that provide more consistent, accurate and relevant search results regardless of the searcher's framing of the query. Marwah Alaofi, Luke Gallagher, Dana McKay, Lauren L. Saling, Mark Sanderson, Falk Scholer, Damiano Spina, Ryen W. White |
SIGIR | 4 |
| 2000 | Potential determinants of heavier internet usage
Lynette Armstrong, James G. Phillips, Lauren L. Saling |
Int. J. Hum. Comput. Stud. | 3 |