MUTIA, BEATA ANDRIANI (2023) IMPLEMENTATION OF SOCIAL NETWORK ANALYSIS OF DISPUTE BETWEEN RUSSIA AND UKRAINE AND TOPIC MODELING USING LDA. Other thesis, UNIVERSITAS KHATOLIK SOEGIJAPRANATA.

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Abstract

Russia's invasion of Ukraine has caused many reactions from people from various parts of the world. These reactions are often expressed in social media, one of which is Twitter. The relationships that occur in users on Twitter will be analyzed using social network analysis. Social Network Analysis is a method used to analyze the relationship structure of a person or social unit. Measuring the closeness between two nodes with other nodes by analyzing the network is centrality. In this study researchers used two degree centrality calculations, namely degree centrality and betweenness centrality. Degree centrality will calculate the number of connections that one node has or. While betweenness centrality is a calculation that is used to show an actor as an intermediary of the relationship between one actor and another in a social network. In this study researchers also included topic modeling using latent direct allocation. Topic modeling using LDA is a statistical technique that can be used to identify topics in a document or corpus. The result of connecting nodes can find the degree of centrality value it shows that spriter99880 is the most influential actor in the network, and glasnostgone is listed as the nodes that have the highest betweenness centrality value. While the results of topic modeling using LDA are there are 10 topics that are often discussed in social media.

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