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            <title xml:lang="en">Studying the Dissemination of the K-core Influence in Twitter Cascades</title>
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                <forename type="first">Sarah</forename>
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            <idno type="halRefHtml">&lt;i&gt;14th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI)&lt;/i&gt;, May 2018, Rhodes, Greece. pp.28-37, &lt;a target="_blank" href="https://dx.doi.org/10.1007/978-3-319-92007-8_3"&gt;&amp;#x27E8;10.1007/978-3-319-92007-8_3&amp;#x27E9;&lt;/a&gt;</idno>
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            <note type="commentary">Part 1: Social Media - Games - Ontologies</note>
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                <title xml:lang="en">Studying the Dissemination of the K-core Influence in Twitter Cascades</title>
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                    <forename type="first">Sarah</forename>
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                    <forename type="first">Mohamed</forename>
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                  <title>14th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI)</title>
                  <date type="start">2018-05-25</date>
                  <date type="end">2018-05-27</date>
                  <settlement>Rhodes</settlement>
                  <country key="GR">Greece</country>
                </meeting>
                <editor>Lazaros Iliadis</editor>
                <editor>Ilias Maglogiannis</editor>
                <editor>Vassilis Plagianakos</editor>
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                  <publisher>Springer International Publishing</publisher>
                  <biblScope unit="serie">Artificial Intelligence Applications and Innovations</biblScope>
                  <biblScope unit="volume">AICT-519</biblScope>
                  <biblScope unit="pp">28-37</biblScope>
                  <date type="datePub">2018</date>
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              <p>The k-core of an information graph is a common measure of a node connectedness in diverse applications. The k-core decomposition algorithm categorizes nodes into k-shells based on their connectivity. Previous research claimed that the super-spreaders are those located on the k-core of a social graph and the nodes become of less importance as they get assigned to a k-shell away from the k-core. We aim to evaluate the influence span of the social media super-spreaders, located at the k-core, in terms of the number of k-shells that their influence can reach. We base our methodology on the observation that the k-core size is directly correlated to the graph size under certain conditions. We explain these conditions and then investigate it further on real-life meme cascades extracted from Twitter. We utilize the correlation to assess the effectiveness of the k-core nodes for influence dissemination. The results of the carried-out experiments show that the correlation exists in our studied real-life datasets. A high correlation existed between the k-core size and the sizes of the inner k-shells in all the examined datasets. However, the correlation starts to decrease in the outer k-shells. Further investigations have shown that the k-shells that were less correlated exhibited a higher presence of spam accounts.</p>
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