Surge of Disaster Rumors on Social Media: Experts Warn Against 'Liking' Unverified Claims
Following a major disaster, posts regarding crime prevention and suspicious individuals in affected areas have rapidly increased on social media platforms. In particular, claims such as "foreign theft rings are gathering in disaster zones" and "suspicious foreigners have been spotted" were widely shared, causing related keywords to trend on X (formerly Twitter).
Among the posts, many users expressed concerns over worsening public safety, calling for increased police patrols, checkpoints, and urging local residents to stay vigilant. However, media reports have revealed that these posts also contain fake images generated by AI and ungrounded rumors (disinformation).
According to experts, during disasters, uncertain information is often spread out of anxiety or well-meaning intentions. To prevent the spread of false information and rumors, experts point out that "for unverified information, it is important to refrain not only from sharing, but also from reacting to it through 'likes' or saving the posts."
Misinformation that stirs up excessive fear and prejudice carries the risk of causing unnecessary confusion at disaster sites. During times of disaster, people are urged to act based on accurate information provided by official institutions such as local governments and police.
The context
In Japan, major natural disasters such as earthquakes often lead to a rapid increase in online rumors targeting foreigners or warning of widespread looting, a pattern seen during past events like the 2011 Great East Japan Earthquake and the 2024 Noto Peninsula Earthquake. While Japanese communities place a high emphasis on mutual vigilance and safety, unverified reports and AI-generated imagery frequently cause unnecessary panic and strain local emergency services. Japanese authorities and digital media experts routinely advise the public to rely exclusively on official announcements from municipal governments and police, warning that even minimal social media engagement like liking or bookmarking can cause harmful algorithm-driven amplification.
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