Evaluation of centrality algorithms for information spread in social networks
| dc.contributor.advisor | Δουλκερίδης, Χρήστος | |
| dc.contributor.author | Οσκιάν, Ναταλί | |
| dc.date.accessioned | 2020-07-23T08:57:20Z | |
| dc.date.available | 2020-07-23T08:57:20Z | |
| dc.date.issued | 2020-06 | |
| dc.identifier.uri | https://dione.lib.unipi.gr/xmlui/handle/unipi/12829 | |
| dc.identifier.uri | http://dx.doi.org/10.26267/unipi_dione/252 | |
| dc.format.extent | 68 | el |
| dc.language.iso | en | el |
| dc.publisher | Πανεπιστήμιο Πειραιώς | el |
| dc.title | Evaluation of centrality algorithms for information spread in social networks | el |
| dc.type | Master Thesis | el |
| dc.contributor.department | Σχολή Τεχνολογιών Πληροφορικής και Επικοινωνιών. Τμήμα Ψηφιακών Συστημάτων | el |
| dc.description.abstractEN | The increased interest in social networks and how the information spread within them, has highlighted the need to identify what makes the nodes that contribute more to the information spread important. Centrality indices are measures of a node’s importance in a given network. Many of those have been proposed over the years, although there is not a common approach on how to use them in the case of information spread maximization. In this study, we evaluate five existing centrality algorithms, based on their performances as centrality measures to select nodes that will spread information across the graph. The centrality algorithms that are evaluated are Degree, Closeness, Betweenness, Eigenvector and PageRank. The results indicate the importance of nodes’ in-degree and of relationships’ direction. Although none of the algorithms outperforms the others in all cases, Degree Centrality has consistently good performance. The algorithm that achieves the lowest spreads of information is Betweenness. | el |
| dc.contributor.master | Ψηφιακά Συστήματα και Υπηρεσίες | el |
| dc.subject.keyword | Graph | el |
| dc.subject.keyword | Big graph | el |
| dc.subject.keyword | Information spread | el |
| dc.subject.keyword | Centrality | el |
| dc.subject.keyword | Social networks | el |
| dc.date.defense | 2020-06-30 |
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Τμήμα Ψηφιακών Συστημάτων
Department of Digital Systems