Modeling Misinformation Diffusion in Social Media: Beyond Network Properties

被引：1
|
作者：
Spezzano, Francesca [1 ]
机构：
[1] Boise State Univ, Comp Sci Dept, Boise, ID 83725 USA
来源：
2021 IEEE THIRD INTERNATIONAL CONFERENCE ON COGNITIVE MACHINE INTELLIGENCE (COGMI 2021) | 2021年
基金：
美国国家科学基金会;
关键词：
misinformation; fake news diffusion; profiling fake news spreaders; computational social science; diffusion of innovation; FAKE NEWS;
D O I：
10.1109/CogMI52975.2021.00030
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, we discuss the current limitations of existing models for misinformation diffusion in social media and present our current work suggesting that other factors beyond network properties play an important node in modeling misinformation spread and profiling fake news spreaders. These factors include news and user characteristics such as user demographics, profile properties, and behavior and activity, and news style and content complexity.
引用
收藏
页码：168 / 171
页数：4
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