Recognizing Human Needs During Critical Events Using Machine Learning Powered Psychology-Based Framework | Zendy

Rajwa Alharthi | Zendy; Benjamin Guthier | Zendy; Abdulmotaleb El Saddik | Zendy

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Recognizing Human Needs During Critical Events Using Machine Learning Powered Psychology-Based Framework

Author(s) -

Rajwa Alharthi,

Benjamin Guthier,

Abdulmotaleb El Saddik

Publication year - 2018

Publication title -

ieee access

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.587

H-Index - 127

ISSN - 2169-3536

DOI - 10.1109/access.2018.2874032

Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation

We propose a psychological need detection framework which automatically identifies people needs and measures their satisfaction level. The framework employs three need models, which are developed using psychological, linguistic, and Twitter-specific features. We evaluate the performance of the proposed models on psychological need data sets which are annotated by psychologists. The models obtained encouraging results: 78.71% in recognizing need content, 81.96% in identifying need type, and 93.56% in measuring need satisfaction level. We use the proposed framework to recognize individual needs and measure their satisfaction level in response to the Florida shooting event, which occurred on February 14, 2018, and the related March for Our Lives event which followed on March 24, 2018. Timeline-based visual and textual representations are generated to explain the motivation behind public reaction and behavior.

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