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Discovering Causality in Suicide Notes Using Fuzzy Cognitive Maps
White, Ethan

2011, MS, University of Cincinnati, Engineering and Applied Science: Computer Engineering.
Suicide has become a significantly prominent issue because high frequencies of occurrences make it one of the top three causes of death for young people in the United States. To prevent suicide attempts, it is important to identify suicidal tendencies in the behavior, speech, or writing of an individual as early as possible. This paper demonstrates one technique of analyzing written material to determine whether or not a person is in a suicidal state. Word frequencies were examined from both suicide and non-suicide documents and translated into inputs to a fuzzy cognitive map (FCM). The FCM determined whether the given input pattern was suicidal or non-suicidal. For the datasets examined, each set was correctly identified by the FCM as suicidal or non-suicidal.
Lawrence Mazlack, PhD (Committee Chair)
John P. Pestian, PhD (Committee Member)
Karen Davis, PhD (Committee Member)
Ali Minai, PhD (Committee Member)
142 p.

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White, E. (2011). Discovering Causality in Suicide Notes Using Fuzzy Cognitive Maps. (Electronic Thesis or Dissertation). Retrieved from https://etd.ohiolink.edu/

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White, Ethan. "Discovering Causality in Suicide Notes Using Fuzzy Cognitive Maps." Electronic Thesis or Dissertation. University of Cincinnati, 2011. OhioLINK Electronic Theses and Dissertations Center. 08 Jul 2015.

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White, Ethan "Discovering Causality in Suicide Notes Using Fuzzy Cognitive Maps." Electronic Thesis or Dissertation. University of Cincinnati, 2011. https://etd.ohiolink.edu/

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