Small Number of Communities in Twitter Keyword Networks

被引：0

作者：

Abraham, Linda ^{[1
]}

Bonato, Anthony ^{[1
]}

Nazareth, Alexander ^{[1
]}

机构：

[1] Ryerson Univ, Toronto, ON, Canada

来源：

COMPLEX NETWORKS & THEIR APPLICATIONS X, VOL 1 | 2022年 / 1015卷

基金：

加拿大自然科学与工程研究理事会;

关键词：

D O I：

10.1007/978-3-030-93409-5_5

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

We investigate networks formed by keywords in tweets and study their community structure. Based on datasets of tweets mined from over seven hundred political figures in the U.S. and Canada, we hypothesize that such Twitter keyword networks exhibit a small number of communities. Our results are further reinforced by considering via so-called pseudo-tweets generated randomly and using AI-based language generation software. We speculate as to the possible origins of the small community hypothesis and further attempts at validating it.

引用

页码：50 / 61

页数：12

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