Eric Nava
by Eric Nava
Near-real-time traffic information is no longer communicated exclusively through traditional news outlets or transportation agency channels. Instead, it is increasingly shared through community-driven social media platforms that have become part of how residents stay informed about roadway conditions, crashes and daily traffic disruptions.
In El Paso, the Instagram account @therealfitfamelpaso has grown to nearly 700,000 followers by sharing near-real-time updates on crashes, road closures, police activity, construction impacts and other events occurring across the region. Much of this information originates from members of the public who tag or message the account with reports from the field. Posts related to unplanned events, such as police activity closures, often generate substantial public attention, typically reaching between 1,000 and 10,000 likes. The account has also become a frequent reference point for local news coverage, with outlets often sourcing its posts when reporting on developing incidents.
For many El Pasoans, the account has become a go-to source for immediate, ground-level information. In some cases, users appear to consult it just as normal as checking traditional navigation platforms such as Google Maps, Apple Maps or Waze.
This raises an important question about how information is shared and how its reliability and usefulness compare with traditional sources.
Understanding How Traffic Information Flows Through Social Platforms
This research focuses on how traffic-related information is shared, consumed, and interpreted through social media, as well as how that information compares with traditional sources such as transportation agencies and news organizations.
A key area of interest is whether crowdsourced, near-real-time updates shared by the public can complement official communication channels and help transportation agencies better understand how information spreads during active traffic events. The work also explores opportunities for collaboration between transportation agencies, emergency responders and media partners to improve the delivery of timely public information.
At its core, the research is centered on “meeting people where they are,” recognizing that many residents already rely on social platforms as part of their daily information ecosystem.
Crowdsourced Reporting and Its Impact on Awareness and Behavior
Much of the content shared on local social media platforms originates directly from the public. Residents often tag or message accounts with photos, videos or descriptions of traffic incidents as they occur, creating a rapid stream of crowd-generated updates.
This type of information flow is often faster than traditional reporting channels. However, it also introduces challenges related to verification, completeness and content appropriateness.
While crowdsourced updates can improve situational awareness in real time, they may also lead users to make rapid decisions based on incomplete or unverified information.
Implications for Agencies and Transportation Planning
For transportation agencies, this evolving information landscape presents both opportunities and challenges. Understanding how the public already receives and shares traffic updates can help identify communication gaps and improve the speed and reach of official messaging through coordinated communication and mitigation strategies.
At the same time, ensuring accuracy and consistency remains critical, particularly as information spreads rapidly through informal channels.
Looking Ahead
As this exploratory work continues, future research may examine how social media data can be integrated with existing traffic monitoring systems, as well as potential partnerships with agencies interested in improving near-real-time communication.
Eric Nava is an associate research scientist with the Center for International Intelligent Transportation Research (CIITR) in TTI’s El Paso Office. This work was funded by the CIITR to examine how social media functions as a crowdsourcing tool for traffic-incident awareness and how it may influence driver behavior and engagement.