ARGH! Automated Rumor Generation Hub

Larry Huynh, Thai Nguyen, Joshua Goh, Hyoungshick Kim, Jin B. Hong

Research output: Chapter in Book/Conference paperConference paperpeer-review

4 Citations (Scopus)


It is still challenging to effectively identify rumors due to rapid changes in people's interests and perceptions. To enhance rumor detectors, we first need to better understand which rumors are effective (in terms of bypassing detection) and their characteristics. In this paper, we introduce ARGH, a novel framework to automatically generate rumors using recent advancements in natural language processing, customized to target and generate specific topics. To show the effectiveness of ARGH, we conducted a user study with 212 participants and analyzed how well humans can detect the rumors generated by ARGH, and we also tested its performance against the state-of-the-art rumor detection model PLAN [17]. Surprisingly, the experimental results demonstrate that the generated rumors are significantly harder to identify as rumors than hand-written rumors, degrading the detection accuracy by both humans and machines by 18.87% and 17.62%, respectively. We believe that ARGH will be a useful tool to obtain high quality and evasive rumor datasets quickly, which is often a tedious and time consuming task. Further, our analysis results provide valuable insight into how to characterize evasive rumors and how they can be generated, which will help to enhance the existing rumor detection techniques.

Original languageEnglish
Title of host publicationCIKM 2021 - Proceedings of the 30th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery (ACM)
Number of pages10
ISBN (Electronic)9781450384469
Publication statusPublished - 26 Oct 2021
Event30th ACM International Conference on Information and Knowledge Management - Gold Coast, Australia
Duration: 1 Nov 20215 Nov 2021

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings


Conference30th ACM International Conference on Information and Knowledge Management
Abbreviated titleCIKM 2021
CityGold Coast


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