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      <title-group>
        <article-title>Persuasive Recommender Systems - Keynote</article-title>
      </title-group>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Markus Zanker</string-name>
          <email>mzanker@unibz.it</email>
          <xref ref-type="aff" rid="aff0">0</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>Free University of Bozen-Bolzano 39100 Bozen-Bolzano</institution>
          ,
          <country country="IT">Italy</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>Recommender Systems (RS) have become indispensable tools to support users when confronted with large collections. They focus the attention of users on a subset of items out of a variety of choices. Therefore RS are inherently persuasive online tools trying to pair users with items that might constitute a better match with their preferences than those choices the users might know already or they could detect on their own without the help of virtual guides. The goal of this talk is therefore to explore the range of influential cues and aspects that have been shown to influence the opinions of users and discuss avenues for further research.</p>
      </abstract>
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      <title>-</title>
      <p>Copyright is held by the author/owner(s).</p>
      <p>EICS’16, June 21-24, 2016, Bruxelles, Belgium.</p>
      <p>
        Outline
Persuasion is generally seen as the intended inducing of
another person to believe something, to do something or to
change attitudes, mood and behavior (compare for instance
to [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ]). Persuasion obviously takes place via communication
and argumentation, but not only. The Elaboration Likelihood
Model (ELM) [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ] has been proposed to explain these
persuasion effects of messages. It principally identifies a main
route towards persuasion that depends on the
characteristics of the message itself, i.e. the quality and strength of
an argument as a main determinant of persuasion effects.
However, in addition there is also consistent empirical
evidence that there is a peripheral route towards persuasion
that depends on various sender and receiver
characteristics. For instance, the willingness and conceptual ability of
the receiver to scrutinize the argument of a message has a
moderating effect on the persuasion, i.e. enhanced scrutiny
of a "strong" message makes the persuasion effect even
stronger while an inhibited ability to scrutinize would have a
weakening effect. Furthermore, additional peripheral cues
such as characteristics of the source of communication like
its credibility or its attractiveness of appearance also have
an effect on the strength and direction of the induced
attitude change. In the context of recommendation systems
Gretzel &amp; Fesenmaier [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ], for instance, pointed out that the
way the user’s preferences are elicited has not only an
effect on how users perceive the process but also influences
their perception of the fit between their preferences and the
recommendations. Thus persuasion happens side by side
with recommendation. In Yoo et al. [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ] we structured these
peripheral clues in the context of product recommendations
that may have an influence on the users’ perception of the
recommendation systems and its proposals into the type
of the RS, factors related to the preference elicitation, the
process and the output and aspects concerning the
embodiment of a recommendation agent. By primarily focusing on
accuracy a lot of recommender systems research ignores
these appearance and interaction dependent aspects of a
RS [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ].
      </p>
      <p>
        This talk therefore gives an overview on the impact of
persuasive traits in the interaction with recommendation
systems [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ] as well as focuses on opportunities for further
research such as explanations of recommendations [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ], the
impact of different design variants of these explanations
such as their style of presentation [
        <xref ref-type="bibr" rid="ref8">8</xref>
        ] or the application of
decision phenomena like decoy or framing effects and their
interaction effects [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ].
      </p>
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