SearchScam:
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Date
2024-12
Journal Title
Journal ISSN
Volume Title
Publisher
Don Mariano Marcos Memorial State University - Mid La Union Campus
Abstract
The growing prevalence of online scams makesthisstudy explored the development of a sentiment-analysis-based system designed to classify online gambling platforms as either legitimate or fraudulent. By employing advanced tools such as the Google Places API. 1VHOIS API. and OpenAI’s natural language processing models, the system effectively analyzed user feedback. metadata, and social media trends to detect scam indicators. Following the CRISP-DM framework, rigorous methodologies for data collection, preprocessing, and analysis were applied, resulting in a system that provided clear and interpretable credibility scores. Validated through the System Usability Scale (SUS) with a score of 71.07, the research highlighted the pivotal role of sentiment analysisin processing unstructured data and enhancing cybersecurity efforts. This work contributed to combating online fraud by offering a practical tool that bridges technological innovation with user safety, fostering trust and security in the digital age.
Description
Full text
Keywords
Application software--Development, Application software, Internet gambling, Sentimentalism, Emotions (Philosophy)
Citation
Daz, B. C. N., Carig, H. G. T., Culaton, J. S., & Urbi, R. F. (2024). SearchScam: Classifying online gambling website or application scams using sentiment analysis. [Unpublished Undergraduate Thesis]. Don Mariano Marcos Memorial State University - Mid La Union Campus, City of San Fernando, La Union. Lakasa ti Sirib, DMMMSU Institutional Repository.