Kanser hastalığı ile ilgili paylaşımlar için Dirichlet ayrımı ile gizli konu modelleme

Volkan ALTINTAŞ, Mehmet ALBAYRAK, Kamil TOPAL
2021 Gazi Üniversitesi Mühendislik-Mimarlık Fakültesi Dergisi  
 Examination of social media platform shares using Natural Language Processing Methods  Examination of the data set with the help of Text Mining techniques  Determining the subheadings in the data set with the Topic Modelling methods Figure A. System Architecture Purpose: The aim of this paper is to reveal the main topics discussed by examining reddit user comments about cancer disease. Theory and Methods: After the preproccesing, user comments are divided into topics with the help of the
more » ... ent dirichlet allocation method. Results: The proposed approach using LDA has created consistent and semantically meaningful topics and clusters from user shares. The obtained topics can not only help people to interpret the texts in a large sharing collection in a way that can be interpreted by human beings but can also help patients and doctors discover new content that may be neglected. Conclusion: The results obtained with the LDA algorithm consist of the diagnosis of cancer disease, treatment process, moral-motivation during the disease period, chemotherapy period and medical support.
doi:10.17341/gazimmfd.734730 fatcat:az7p6imurnbfjf6lsogqsnl6ma