Document Type
Poster
Abstract
The research of information diffusion on social networks is commonly investigated through the application of social network analysis, utilizing graph theory. This pro-posed study aims to classify diverse forms of information dissemination on Twitter using topological data analysis techniques. Specifically, by simulating each instance of information diffusion on a predefined graph network across distinct time intervals, tracing the underlying homologies, and analyzing these filtrations via clustering methods, the project seeks to categorize varied information propagation on Twitter. This work is furthering research by the Gonzaga Topological Data Analysis Research Group which used this methodology to analyze airline fight patterns.
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Publication Date
2023
Keywords
social network analysis, graph theory, topological data analysis, information propagation, Twitter
Disciplines
Mathematics
Recommended Citation
Garcia-Camargo, Leon; Recker, Malia; and Nguyen, Matt, "Topological Data Analysis of Information Spread on Twitter" (2023). Math Student Scholarship. 3.
https://repository.gonzaga.edu/mathstudentschol/3
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