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Perception Analysis: A Knowledge Discovery and Inference Generation Approach to Crisis Informatics

Okpala, Izunna
http://orcid.org/0000-0003-2502-3965
http://rave.ohiolink.edu/etdc/view?acc_num=ucin1692283429734113

Abstract Details

2023, PhD, University of Cincinnati, Education, Criminal Justice, and Human Services: Information Technology.
This study explores perception analysis via the lenses of machine learning and natural language processing. To reflect the efficacy of machines in analyzing crisis situations, the research incorporated the concepts of knowledge discovery and inference generation through three interconnected studies. The first study demonstrates the capability of an intelligent system to capture human perception toward COVID-19. This intelligent system features text preprocessing, identification of cues in a sentence structure, and the use of the TextBlob tool to gauge the perception of the identified cues. The second study tackled one of the limitations of the first research - the issue of negation and multiple negatives in natural language processing. To solve this problem, the study employed a negation disambiguation framework when dealing with negations and multiple negatives. The third study combines the benefits of the first two studies in gauging human perception by taking into account sentence structure, contextualization, text transformation, and, most importantly, people's views with respect to a causative agent (entity). The three studies show a transition from one solution to another, an indication that an automated system can achieve better accuracy in classifying crisis-related data and ultimately improve response techniques available to various stakeholders.
Jess Kropczynski, Ph.D. (Committee Chair)
Chengcheng Li, Ph.D. (Committee Member)
Shane Halse, Ph.D. (Committee Member)
Kelly Cohen, Ph.D. (Committee Member)
113 p.
Information Technology
Perception Analysis; Machine Learning; Natural Language Processing; Negation Detection; Crisis Informatics; Situational awareness

Recommended Citations

Citations

  • Okpala, I. (2023). Perception Analysis: A Knowledge Discovery and Inference Generation Approach to Crisis Informatics [Doctoral dissertation, University of Cincinnati]. OhioLINK Electronic Theses and Dissertations Center. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1692283429734113

    APA Style (7th edition)

  • Okpala, Izunna. Perception Analysis: A Knowledge Discovery and Inference Generation Approach to Crisis Informatics. 2023. University of Cincinnati, Doctoral dissertation. OhioLINK Electronic Theses and Dissertations Center, http://rave.ohiolink.edu/etdc/view?acc_num=ucin1692283429734113.

    MLA Style (8th edition)

  • Okpala, Izunna. "Perception Analysis: A Knowledge Discovery and Inference Generation Approach to Crisis Informatics." Doctoral dissertation, University of Cincinnati, 2023. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1692283429734113

    Chicago Manual of Style (17th edition)

ucin1692283429734113
80
© 2023, some rights reserved.Creative Commons License Perception Analysis: A Knowledge Discovery and Inference Generation Approach to Crisis Informatics by Izunna Okpala is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License. Based on a work at etd.ohiolink.edu.
This open access ETD is published by University of Cincinnati and OhioLINK.