Crowdsourced social media monitoring system development.

Details

• Creators:
  Kumar, Amit ; Ross, Catherine L. ; Karner, Alex A. ; Katyal, Rohan
• Corporate Creators:
  Georgia Institute of Technology. Center for Quality Growth and Regional Development
• Corporate Contributors:
  Georgia. Department of Transportation. Office of Research ; United States. Federal Highway Administration
• Subject/TRT Terms:
  • Incident management
  • Highway traffic control systems
  • Social media Management
  • Social Media Monitoring
  • Incident Management
  • Crowdsourcing
• Publication/ Report Number:
  FHWA-GA-17-1614
• Resource Type:
  Tech Report
• Geographical Coverage:
  Georgia;United States
• Corporate Publisher:
  Georgia. Department of Transportation. Office of Research
• Abstract:
  Crowdsourcing is a relatively new area of research, but it is already generating an enormous amount of ; interest among both researchers and practitioners, and is finding applications in multiple domains. It is ; particularly useful for efficient traffic management and increasing public participation. Many state DOTs ; are already using crowdsourced technologies and others are exploring its applications for traffic ; management. Researchers are using sensor-rich mobile phones and online social networks for fetching ; data from network users. Despite recent advancements, there remain gaps between the state of the art and ; practice that need to be bridged. Programs like the Waze Connected Citizens Program and Strava Metro ; Data Program are success stories in practice. This study explores the implementation of crowdsourced ; traffic management by Georgia DOT (GDOT) and the challenges specific to them. The reliability of data ; and filtering high volumes of information were found to be the two primary concerns. The team proposed ; a system which can potentially tackle those challenges. The system consists of a mobile application and a ; text mining application that together leverage the existing Twitter technology stack. Based on interviews ; with traffic management professionals and a visit to GDOT, the report contains recommendations that ; would improve the workflow at the TMC. Computer vision, data management and social media analytics ; would be particularly beneficial to decrease operator burden. A system with multiple sources of ; information integrated into one would be particularly beneficial. We are on the cusp of a revolution with ; respect to big data and crowdsourcing. This is the ideal time for GDOT to invest in crowdsourcing ; technologies to reap the benefits in the future.
  More +
• Format:
  PDF
• Funding:
  2014-32, RES PROJ 16-14
• Download URL:
  https://rosap.ntl.bts.gov/view/dot/32726/dot_32726_DS1.pdf
• File Type:
  [PDF - 2.38 MB]
• Collection(s):
  US Transportation Collection
• Main Document Checksum:
  urn:sha-512:601c005219c2ff19506602699f879be97a3e3c62466ad5de2ea657970f48e6c49b868c29c4c55b3da8d55d9b64c3e5701847ac8f165e470eca64999fde577ab2