Mapping social media analytics in firearm injury exposure research: a scoping review

To examine how social media analytics have been applied in research on firearm injury exposure, with a focus on informatics approaches, analytical methodologies, and public health surveillance applications.

Following the PRISMA-ScR framework for scoping reviews, we systematically searched 5 databases (Web of Science, Scopus, PubMed, IEEE Xplore, ACM Digital Library) for studies published 2014-2025 that used social media analytics to investigate firearm injury exposure. The most recent search was conducted on February 18, 2025. Two independent reviewers screened studies using standardized criteria and extracted study characteristics via Covidence. Inter-rater reliability was found to be (Cohen's κ = 0.63). Of 742 initial records, 16 studies met the inclusion criteria.

All included studies (16/16; 100%) used X (formerly Twitter) as the data source. Analytical approaches were natural language processing (n = 12), topic modeling (n = 8), and sentiment analysis (n = 6). Most studies were US-based (n = 12) and examined direct exposure (eg, witnessing shootings) and indirect exposure (eg, media coverage). Key informatics applications included sentiment detection, temporal discourse pattern analysis, and computational methods for evaluating community-level impacts.

Findings revealed significant methodological homogeneity, with overreliance on X and limited use of longitudinal designs. Implementations of analytics methods varied considerably. Lack of platform diversity and standardization limits generalizability and integration with public health surveillance systems, impeding translation into policy and intervention.

Social media analytics represent a promising tool for advancing public health informatics related to firearm injuries. Future research should employ platform diversity, longitudinal approaches, and computational metrics to enhance integration with health information systems.