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    <title>Networks | Akhilesh Tumu</title>
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    <description>Networks</description>
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      <title>Networks</title>
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      <title>Cascading Opinions: How Small Network Tweaks Shift Consensus</title>
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      <pubDate>Sun, 28 Apr 2024 00:00:01 +0000</pubDate>
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      <description>&lt;p&gt;This paper analyzes the potential influence of an entity with network-level access (network designer) on consensus opinions formed within networks, analogous to a back-end social media algorithm strategically altering content recommendations. Using the DeGroot opinion dynamics model, we study how a bounded network designer can perturb inter-agent influence weights such that consensus is shifted towards a specific target opinion. We identify simple, efficient algorithms for this influence problem and use simulations on toy examples and real network data to examine the relationship between final consensus value and the bounds on the network designer. We find that even when tightly bounded, the network designer is able to exert considerable power on the final consensus, and that there appears to be a logistic relationship between the logarithm of the bound value and the final consensus opinion. We conclude by discussing how the actions induced by these algorithms may correlate with modern social media algorithms, affecting critical stages of the opinion formation process.&lt;/p&gt;
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      <title>Robust Learning in Networks</title>
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      <pubDate>Mon, 01 May 2023 00:00:00 +0000</pubDate>
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