Re ection Machines Requirements to prevent the e ects of micro-targeting in political scenarios
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2022-02-27
Language
en
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Abstract
Over the past decade, the focus of political campaigns has shifted more
and more towards social media and the use of technology. With the use of
psychographics, micro-targeting can be used to manipulate voters towards
a decision. One of the most recent examples for this application is the
Cambridge Analytica (CA) scandal in the 2016 US elections. They sent
out personalized messages to indecisive voters to manipulate them, which
seemingly helped Donald Trump win this election.
This thesis aims to provide a speci cation of a re
ection machine (RM)
that is able to prevent those manipulation e ects by presenting re
ection
messages to a user. RMs are similar to decision support systems, however,
they do not aim to provide a correct solution to the user but enhance the re-
ection process by proposing a question or statement questioning the user's
decision. In the domain of political voting scenarios the re
ection process
is not enhanced by questioning a decision but by raising awareness of possible
micro-targeting proactively. It is examined which requirements such
RM could have when it is to be implemented. This entails the types of
questions, the information needed and the role of the user's information.
To demonstrate the research, a thought experiment with conceptual users
from di erent personality spectra is presented and a mock-up simulation of
an RM to show the enhancement of the re
ection process is executed. The
evaluation shows that there is potential in RMs in relation to raising awareness
of micro-targeted political messages, however more research is yet to
be done in this domain.
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Faculteit der Sociale Wetenschappen