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dc.contributor.author
Verginer, Luca
dc.contributor.author
Vaccario, Giacomo
dc.contributor.author
Ronzani, Piero
dc.date.accessioned
2023-12-05T14:43:46Z
dc.date.available
2023-12-04T13:45:57Z
dc.date.available
2023-12-05T14:43:46Z
dc.date.issued
2023-09-21
dc.identifier.other
10.31235/osf.io/ajusq
en_US
dc.identifier.uri
http://hdl.handle.net/20.500.11850/645338
dc.identifier.doi
10.3929/ethz-b-000645338
dc.description.abstract
We explore human herding in a strategic setting where humans interact with automated entities (bots) and study the shift in the behavior and beliefs of humans when they are aware of interacting with bots. The strategic setting is an online minority game, where 1,997 participants are rewarded for following the minority strategy. This setting permits distinguishing between irrational herding and rational self-interesta fundamental challenge in understanding herding in strategic contexts. Moreover, participants were divided into two groups: one informed of playing against bots (informed condition) and the other unaware (uninformed condition). Our findings revealed that while informed participants adjusted their beliefs about bots' behavior, their actual decisions remained largely unaffected. In both conditions, 30% of participants followed the majority, contrary to theoretical expectations of no herding. This study underscores the persistence of herding behavior in human decision-making, even when participants are aware of interacting with automated entities. The insights provide profound implications for understanding human behavior on digital platforms where interactions with bots are common.
en_US
dc.format
application/pdf
en_US
dc.language.iso
en
en_US
dc.publisher
Center for Open Science
en_US
dc.rights.uri
http://creativecommons.org/licenses/by-nd/4.0/
dc.title
The Robotic Herd: Using Human-Bot Interactions to Explore Irrational Herding
en_US
dc.type
Working Paper
dc.rights.license
Creative Commons Attribution-NoDerivatives 4.0 International
ethz.journal.title
SocArXiv
ethz.size
33 p.
en_US
ethz.publication.place
Charlottesville, VA
en_US
ethz.publication.status
published
en_US
ethz.leitzahl
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03682 - Schweitzer, Frank / Schweitzer, Frank
en_US
ethz.leitzahl.certified
ETH Zürich::00002 - ETH Zürich::00012 - Lehre und Forschung::00007 - Departemente::02120 - Dep. Management, Technologie und Ökon. / Dep. of Management, Technology, and Ec.::03682 - Schweitzer, Frank / Schweitzer, Frank
ethz.date.deposited
2023-12-04T13:45:57Z
ethz.source
BATCH
ethz.eth
yes
en_US
ethz.availability
Open access
en_US
ethz.rosetta.installDate
2023-12-05T14:43:47Z
ethz.rosetta.lastUpdated
2024-02-03T07:52:52Z
ethz.rosetta.versionExported
true
ethz.COinS
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