SIDetect : A Web-Base Application for Detecting Suicidal Ideations (SI) Using Natural Language Processing and Machine Learning / Neil Michael D. Cañas, Carlo M. Salva, Saeymond Charles N. Serrano, Jihad M. Yusoph.

By:

Cañas, Neil Michael D

Contributor(s):

Material type: Text

TextManila : Technological University of the Philippines, 2023Description: x, 124 pages : illustrations ; 29 cm. + 1 CD-ROM (4 3/4 in.)Content type:

text

Media type:

unmediated

Carrier type:

volume

Subject(s):

Suicidal behavior -- Computer programs

LOC classification:

BTH QA 76 C36 2023

Dissertation note: College of Science -- Bachelor of Science in Computer Science, Technological University of the Philippines, 2023. Abstract: This thesis introduces SIDetect, a web-based application that uses machine learning (ML) and natural language processing (NLP) methods to identify suicidal ideations (SI). The system uses natural language processing (NLP) to extract pertinent information from user-generated text, which is then examined using machine learning (ML) algorithms to find patterns that suggest the presence of suicidal ideations. A dataset of user-generated text with SI and non-SI instances was used to assess the system. It was developed using Visual Studio Code, Open API, and Python as the programming language. The user interface of the system was also assessed and found to be intuitive and user-friendly. The system was evaluated using ISO 25010 criteria for quality assurance, with a total of 23 respondents consisting of IT/CS, Psychology students, and professionals from the IT and Psychology field. According to the evaluation's findings, SIDetect achieved an overall score of 3.55, indicating a Highly Acceptable rating.--Author's Abstract

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Holdings
Item type	Current library	Shelving location	Call number	Copy number	Status	Notes	Date due	Barcode
Bachelor's Thesis COS	TUP Manila Library	Thesis Section-2nd floor	BTH QA 76 C36 2023 (Browse shelf(Opens below))	c.1	Not for loan	For Room Use Only		BTH0003478

Thesis (Undergraduate)

College of Science -- Bachelor of Science in Computer Science,
Technological University of the Philippines,
2023.

Includes bibliographical references.

This thesis introduces SIDetect, a web-based application that uses machine learning (ML) and natural language processing (NLP) methods to identify suicidal ideations (SI). The system uses natural language processing (NLP) to extract pertinent information from user-generated text, which is then examined using machine learning (ML) algorithms to find patterns that suggest the presence of suicidal ideations. A dataset of user-generated text with SI and non-SI instances was used to assess the system. It was developed using Visual Studio Code, Open API, and Python as the programming language. The user interface of the system was also assessed and found to be intuitive and user-friendly. The system was evaluated using ISO 25010 criteria for quality assurance, with a total of 23 respondents consisting of IT/CS, Psychology students, and professionals from the IT and Psychology field. According to the evaluation's findings, SIDetect achieved an overall score of 3.55, indicating a Highly Acceptable rating.--Author's Abstract

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