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Daniel Goetz

dblp:324/3587 · DBLP profile ↗
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1ranked-venue papers
1as first author
1since 2021 · last 2022
—ORCID · unresolved

Domains — the database's venue-derived domains; a paper can count in several

Artificial intelligence and machine learning · 1 · 1 first-author · 1 since 2021Theory of computation · 1 · 1 first-author · 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.

Interdisciplinary, comprehensive, and emerging computing
1 paper
Computational social science and digital humanities · 100%
Databases, data mining, and information retrieval
1 paper
Web and social media mining · 100%
Theoretical computer science
1 paper
Algorithmic game theory and mechanism design · 100%

Topics — the 2 heaviest of 3, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Computational social science and digital humanities
social influence		 0.612022
Peer Effects from Friends and Strangers: Evidence from Random Matchmaking in an Online Game · EC 2022
Web and social media mining
social network analysis		 0.612022
Peer Effects from Friends and Strangers: Evidence from Random Matchmaking in an Online Game · EC 2022

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

regression · 1.7randomized experiment · 1.7
YearPublicationVenuePosition
2022 Peer Effects from Friends and Strangers: Evidence from Random Matchmaking in an Online Game
abstract
In this paper, we quantify the social interaction (peer) effect from friends' and strangers' product adoption decisions. While a large literature has separately documented the importance of the observed adoptions of friends [1,2,8,9] and strangers [3,4,6,7] for spurring further product adoption, by analyzing both together we are able to benchmark their relative magnitudes, evaluate how these two types of peer effects interact, and provide managerial guidance on how firms can jointly leverage both types of peer effects in product seeding campaigns.
Daniel Goetz, Wei Lu 0020
 EC1