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Lauren Solomon

dblp:13/7983 · DBLP profile ↗
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1ranked-venue papers
0as first author
0since 2021 · last 2010
—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.

Databases, data mining, and information retrieval
1 paper
Information retrieval · 100%
Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational social science and digital humanities · 100%

Topics — the 3 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Information retrieval
online advertising
0.112010
Gender demographic targeting in sponsored search · CHI 2010
Information retrieval › online advertising
sponsored search
0.112010
Gender demographic targeting in sponsored search · CHI 2010
Computational social science and digital humanities › marketing
consumer behavior
0.012010
Gender demographic targeting in sponsored search · CHI 2010

Methods — techniques the papers use, named apart from their topics

statistical hypothesis testing · 0.2log analysis · 0.2
YearPublicationVenuePosition
2010 Gender demographic targeting in sponsored search
abstract
In this research, we evaluate the effect of gender in analyzing the performance of sponsored search advertising. We examine a log file with data comprised of nearly 7,000,000 records spanning 33 consecutive months of a search engine marketing campaign from a major US retailer. We classify key phrases selected for the campaign with a probability of being targeted for a specific gender and then compare the consumer actions using the critical sponsored search metrics of impressions, clicks, cost-per-click, sales revenue, orders, and items sold. Findings from our analysis show that the gender-orientation of the key phrase is a significant determinant in predicting behaviors and performance, with statistically different consumer behaviors for all attributes as the probability of a male or female keyword phrase changes. However, gender neutral phrases perform the best overall, calling into question the benefits of demographic targeting. Insight from this research could result in sponsored results being more effectively targeted to searchers and potential consumers.
Jim Jansen, Lauren Solomon
CHI2