Demo Data from VLDB 2026 / reviewers in the wild / expert
Timothy Havens
dblp:119/8009
· DBLP profile ↗
1ranked-venue papers
0as first author
0since 2021 · last 2019
—ORCID · unresolved
Domains — the database's venue-derived domains; a paper can count in several
Databases, data management, data science and information retrieval · 1Applied, interdisciplinary, general and emerging 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% |
Topics — the 2 heaviest of 2, each with the papers that count most for it
| Topic | Weight | Papers | Last | Evidence papers |
|---|---|---|---|---|
Information retrieval
personalized search |
0.4 | 1 | 2019 | Measuring Political Personalization of Google News Search · WWW 2019 |
Information retrieval › web search
search personalization |
0.4 | 1 | 2019 | Measuring Political Personalization of Google News Search · WWW 2019 |
Methods — techniques the papers use, named apart from their topics
sock-puppet auditing · 0.4
| Year | Publication | Venue | Position |
|---|---|---|---|
| 2019 | Measuring Political Personalization of Google News SearchabstractThere is a growing concern about the extent to which algorithmic personalization limits people's exposure to diverse viewpoints, thereby creating “filter bubbles” or “echo chambers.” Prior research on web search personalization has mainly reported location-based personalization of search results. In this paper, we investigate whether web search results are personalized based on a user's browsing history, which can be inferred by search engines via third-party tracking. Specifically, we develop a “sock puppet” auditing system in which a pair of fresh browser profiles, first, visits web pages that reflect divergent political discourses and, second, executes identical politically oriented Google News searches. Comparing the search results returned by Google News for distinctly trained browser profiles, we observe statistically significant personalization that tends to reinforce the presumed partisanship. Huyen T. Le, Raven Maragh, Brian Ekdale, Andrew High, Timothy Havens, Zubair Shafiq |
WWW | 5 |