MEWS: Real-time Social Media Manipulation Detection and Analysis

被引：0

作者：

Ford, Trenton W. ^{[1
]}

Yankoski, Michael ^{[1
]}

Theisen, William ^{[1
]}

Henry, Tom ^{[1
]}

Khashman, Farah ^{[1
]}

Dearstyne, Katherine R. ^{[1
]}

Weninger, Tim ^{[1
]}

Thomas, Pamela Bilo ^{[2
]}

机构：

[1] Univ Notre Dame, Dept Comp Sci & Engn, Notre Dame, IN 46530 USA

[2] Univ Louisville, Dept Comp Sci & Engn, Louisville, KY 40292 USA

来源：

NEURIPS 2021 COMPETITIONS AND DEMONSTRATIONS TRACK, VOL 176 | 2021年 / 176卷

关键词：

Social media; misinformation; graph theory; near real-time detection;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This article presents a beta-version of MEWS (Misinformation Early Warning System). It describes the various aspects of the ingestion, manipulation detection, and graphing algorithms employed to determine-in near real-time-the relationships between social media images as they emerge and spread on social media platforms. By combining these various technologies into a single processing pipeline, MEWS can identify manipulated media items as they arise and identify when these particular items begin trending on individual social media platforms or even across multiple platforms. The emergence of a novel manipulation followed by rapid diffusion of the manipulated content suggests a disinformation campaign.

引用

页码：325 / 329

页数：5

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