Threat Assessment Techniques for Digital Data
Abstract
The objective of the proposed work is to lay the theoretical and methodological foundations for detecting threats using social media data. Social media platforms can serve as a rich source of information for early threat detection. By analyzing patterns, keywords, and trends, the military can identify potential threats before they materialize. In principle, artificial intelligence software can analyze social media data to accurately capture #emerging narratives# and generate intelligence reports. This would allow military forces to predict and neutralize threats if needed.Current social media techniques, whether or not they are enabled by artificial intelligence, are limited in their ability to detect threats. In part, this is due to a lack of a deep theoretical understanding of how online threats are manifested in social media, particularly at the community level. From a societal perspective, the issue is not whether an individual is becoming violent or poses a threat, but whether aculture that accepts violence as a solution or a culturethat feels threatened is emerging. To gain this understanding it is critical to first understand how hate, a potential for violence, for protest, and so on present themselves # at a community level. It is necessary to understand when talk in social media is just talk, and when it is a precursor to violence # not for an individual but for a group. We propose a basic line of research to determine whether at the community level, one can detect potential threats. e community writ large in ways that focus on the extreme and not normal debate.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 08, 2024
- Source ID
- N000142412414
Entities
People
- Kathleen Carley
Organizations
- Carnegie Mellon University
- Office of Naval Research
- United States Navy