Scanigo: A Social Media Analytics Toolkit

Progeny developed a social media analytics toolkit called Scanigo under an ONR SBIR N121-092. Scanigo provides a methodology and computer aided approach for identifying critical information from social media for disaster responders. Scanigo implements an Ontology-Based Information Extraction (OBIE) methodology that significantly reduces the amount of information presented to the analysts, based on computed relevance, information overload is reduced by orders-of-magnitude while passing relevant information. Scanigo has been in use supporting real-world disaster since 2012 with results of less than 1% reduction of the total data to actionable information, relevant to the domain. The purpose of this Phase II is to significantly improve Scanigo's modularity, adaptability and performance. In addition, to demonstrate utility for use-cases that supports FEMA's emergency response operations. Planned improvements include: additional data sources; componentization; NoSQL database migration; knowledge extraction; ontology learning; ontology management; and cloud deployment. The primary purpose of componentization is to support various integration opportunities that already have a social media monitoring or analysis platform. For example, the OBIE pipeline that reduces social media streams in real-time based on relevance can be integrated into existing data flow architectures. The common theme of the planned improvements is scale. Componentization will allow Scanigo to scale to other integration opportunities. The ontology improvements will allow Scanigo to scale to other domains. Implementing ontology learning and management allows end users to perform their own domain customization, scaling to other domains. And finally, the performance improvements and a cloud deployment will allow Scanigo to scale to a global market.