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Multi-lingual Social-media Crowd Manipulation Detector (MSCMD)

Award Information
Agency: Department of Defense
Branch: Navy
Contract: N68335-19-C-0357
Agency Tracking Number: N19A-024-0051
Amount: $144,888.00
Phase: Phase I
Program: STTR
Solicitation Topic Code: N19A-T024
Solicitation Number: 19.A
Solicitation Year: 2019
Award Year: 2019
Award Start Date (Proposal Award Date): 2019-06-03
Award End Date (Contract End Date): 2019-12-09
Small Business Information
3031 Tisch Way Suite 1000
San Jose, CA 95128
United States
DUNS: 848536975
HUBZone Owned: No
Woman Owned: No
Socially and Economically Disadvantaged: Yes
Principal Investigator
 Hassan Alam Hassan Alam
 (408) 249-4126
Business Contact
 Hassan Alam
Phone: (408) 249-4126
Research Institution
 Massachusetts Institute of Technology
 Robert Berwick Robert Berwick
77 Massachusetts AVeneu
Cambridge, MA 02139
United States

 (617) 254-1000
 Nonprofit College or University

In this SBIR, BCL proposes developing a Multi-lingual Social-media Crowd Manipulation Detector (MSCMD). The MSCMD will use natural language processing techniques to detect terms that arouse emotion using information out of context to trigger reaction from the audience and move them to act.The MSCMD will operate in Asian languages using a Natural Language Processor for each language. The MSCMD will then parse the text and transforms them into a parse tree with parts of speech tagging. The parse tree will then be tagged for features that have high emotional content, and an emotional feature model will be applied to determine the type of action the text is attempting to raise.A machine learning model will then be applied to the collected data to develop adaptive models that can detect Crowd Manipulation.In Phase I, BCL will research the feasibility of using NLP techniques and psychological markers to detect Social Media Manipulation in the Asia-Pacific region.In Phase II, BCL will develop a machine learning engine that automatically learns what emotions are being used to Manipulate Social Media.

* Information listed above is at the time of submission. *

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