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Multimodal Anomalous Clusters over Internet Tweet Data

Student: Ryabov Artem

Supervisor: Boris Mirkin

Faculty: Faculty of Computer Science

Educational Programme: Applied Mathematics and Information Science (Bachelor)

Year of Graduation: 2021

In this work, we analyze two sets of multi-way data: the relationship of scientific publications with each other and the relationship of political views, life positions and literary preferences based on the dataset of users of the social network VKontakte. The data was transformed into a multi-way format, after which the methods of cluster analysis were applied to them. The clusters found by the algorithms were conceptually and meaningfully interpreted. The work contains 25 pages, 4 chapters, 12 references. Keywords: cluster analysis, multiway data, p-cluster, social networks.

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