Bomb Threat Tracker: Live U.S. Map

Methodology: Incidents are pulled from wire coverage (Bing News / Google News) of specifically-named U.S. bomb-threat reports and geocoded to a city using the U.S. Census Bureau’s public geocoder. City/county demographic figures (population, Black/African American share, median household income) come from the Census Bureau’s American Community Survey 5-Year Estimates for that county. A story is only mapped when a specific city is named in the reporting and successfully geocoded — stories without a confirmed location are still listed as reports but not plotted. This tracker counts reported threats, not confirmed devices; most bomb threats are hoaxes, and each entry links to its original source for verification.

How this tracker works

What it tracks: news about bomb threats reported in the United States.
Where headlines come from: a Google News search for “bomb threat” covering the past two days; a headline must say “bomb threat,” and stories from outside the U.S. are excluded.
What it adds and doesn’t: each entry is the outlet’s own headline, linked to the original. Nothing is rewritten or summarised by AI.
Labels: tags say what kind of source a story comes from (official source, wire service, national, local or international outlet, academic source, or social media post). They are not ratings of accuracy or trust. Opinion pieces are tagged OPINION and kept out of the Latest box.
Updates: twice a day, at about 8:30 a.m. and 8:30 p.m. Central. The Latest box shows the four newest non-opinion stories, one report per story, with a count of other outlets that covered it.
Current source mix (last 25 entries): news outlet 13, local outlet 8, national outlet 3, social media post 1, from 25 different outlets.
Spot an error? Tell us and we will correct it.

Research behind these features

Curry, A. L., & Stroud, N. J. (2021). The effects of journalistic transparency on credibility assessments and engagement intentions. Journalism, 22(4). Explaining how and why a story was produced raised readers’ credibility ratings, across political ideologies. This is why each tracker explains its sourcing and filters.
Otis, A. (2024). The effects of transparency cues on news source credibility online: An investigation of ‘opinion labels’. Journalism. Labelling opinion content on story previews increased the perceived credibility of the source. Opinion pieces here are labelled and kept out of the Latest box.
Aslett, K., et al. (2022). News credibility labels have limited average effects on news diet quality and fail to reduce misperceptions. Science Advances, 8(18). Trust ratings on sources did not, on average, change what people read or believe. So the tags here describe what kind of source a story comes from, not whether to trust it.
Wineburg, S., & McGrew, S. (2019). Lateral reading and the nature of expertise. Teachers College Record, 121(11). Professional fact-checkers judge a claim by quickly checking what other sources say. Each latest story links to other coverage of the same headline.
Pennycook, G., et al. (2021). Shifting attention to accuracy can reduce misinformation online. Nature, 592, 590–595. A brief prompt to think about accuracy improved the quality of news people chose to share. The Latest box ends with that prompt.