{"doi":"10.1101/2022.07.15.22276403","title":"How Americans encounter guns: Mixed methods content analysis of YouTube and internet search data","abstract":"Abstract Firearm-related injury and death is a serious public health issue in the U.S. As more Americans consume news and media online, there is growing interest in using these channels to prevent firearm-related harms. Understanding the firearm-related narratives to which consumers are exposed is foundational to this work. This research used the browsing behavior of a representative sample of American adults to identify seven naturally occurring firearm-related content ecosystems on YouTube, and the demographics and internet search patterns of users affiliated with each ecosystem. Over the 9-month study period, 72,205 panelists had 16,803,075 person-video encounters with 7,274,093 videos. Among these, 282,419 videos were related to firearms. Using fast greedy clustering, we partitioned users and channel interactions into seven distinct channel-based content ecosystems that reached more than 1/1000 YouTube users per day. These ecosystems were diverse in reach, users, and content (e.g., guns for self-protection vs. guns for fun). On average, 0.5% of panelists performed a firearm-related internet search on a given day. The vast majority of these searches were related to mass shootings or police-involved shootings (e.g., “active shooter”), and virtually none were about more common firearm harm such as suicide. Searches for firearm safety information were most common among panelists affiliated with the “Hunting & Fishing” and “Guns & Gear” ecosystems, which were watched primarily by older, white men. These findings identify an opportunity for analyzing firearm-related narratives and tailoring firearm safety messaging for users affiliated with specific online content ecosystems. Highlights We used a mixed methods network analysis of YouTube users’ viewing patterns and identified seven distinct firearm-related content ecosystems. Ecosystems vary by reach, audience demographics, and audience firearm-related search patterns. The ecosystems contain a wide variety of narratives about firearm use, safety, and potential harms. Understanding the diverse narratives across these ecosystems, their respective audiences and audience search patterns can inform future work to reduce firearm-related harms and increase safety.","journal":"medRxiv","year":2022,"id":309928,"datarank":0.0,"base_score":0.0,"endowment":0.0,"self_citation_contribution":0.0,"citation_network_contribution":0.0,"self_endowment_contribution":0.0,"citer_contribution":0.0,"corpus_percentile":null,"corpus_rank":null,"citation_count":0,"citer_count":0,"citers_with_citation_signal":0,"citers_with_endowment":0,"datacite_reuse_total":0,"is_dataset":false,"is_dataset_confidence":0.9476,"is_data_producer":false,"deposit_databanks":null,"is_oa":true,"file_count":0,"downloads":0,"has_version_chain":false,"published_date":"2022-01-01","fair_score":null,"fair_percentile":null,"algorithm_id":"datarank_citation_only_1hop_v6","ranking_scope":"data_only","authors":[{"id":926196,"name":"Frederica R. Conrey","orcid":null,"position":1,"is_corresponding":false},{"id":925651,"name":"Leah Perkinson","orcid":"0009-0009-9326-0197","position":2,"is_corresponding":false},{"id":925652,"name":"Stefanie Friedhoff","orcid":"0000-0001-6719-9585","position":3,"is_corresponding":false},{"id":926197,"name":"Rory Smith","orcid":null,"position":4,"is_corresponding":false},{"id":925653,"name":"Claire Wardle","orcid":"0000-0003-4597-8574","position":5,"is_corresponding":false},{"id":424609,"name":"Megan L. Ranney","orcid":"0000-0002-8450-9642","position":0,"is_corresponding":true}],"reference_count":40,"raw_metadata":{"citation_network_status":"fetched"},"created_at":"2026-07-19T00:33:15.860993Z","pmid":null,"pmcid":null,"fwci":null,"citation_percentile":null,"influential_citations":0,"oa_status":null,"license":null,"views":0,"total_file_size_bytes":0,"version_count":0,"fair_f":null,"fair_a":null,"fair_i":null,"fair_r":null,"fair_zscore":null,"fair_rationale":null,"fair_model":null,"fair_agent_version":null,"fair_fulltext_source":null,"fair_has_llm":null,"fair_computed_at":null,"clinical_trials":[],"software_tools":[],"db_accessions":[],"linked_datasets":[],"topics":[]}