Detecting depression using K-Nearest Neighbors (KNN) classification technique

M. R. Islam, Abu Raihan M Kamal, Naznin Sultana, Robiul Islam, Mohammad Ali Moni, A. Ulhaq

Research output: Book chapter/Published conference paperConference paperpeer-review

34 Citations (Scopus)

Abstract

Social networks have developed as a promising point for everybody to communicate with their interested friend and share their opinions, photos, and videos. Also, it has been an upcoming research field and has picked an established position globally. In this paper, we considered depression problems among various Facebook users. Already, a number of researchers have studied and applied many techniques to detect depression, but still need to detect accurately from social network data. So, we investigate the possibility to utilize Facebook data and apply KNN (k-nearest neighbors) classification technique for detecting depressive emotions. We do believe that our investigation and approach might be helpful to raise consciousness in online social network users.
Original languageEnglish
Title of host publication2018 International Conference on computer, communication, chemical, material and electronic engineering, IC4ME2 2018
PublisherIEEE Xplore
Number of pages4
ISBN (Electronic)9781538647752
ISBN (Print)9781538647769
DOIs
Publication statusPublished - 20 Sep 2018
Event2018 International Conference on Computer, Communication, Chemical, Material and Electronic Engineering : IC4ME2 - University of Rajshahi, Rajshahi, Bangladesh
Duration: 08 Feb 201809 Feb 2018
https://www.aconf.org/conf_147728.html
http://dept.ru.ac.bd/ic4me2/2018/

Conference

Conference2018 International Conference on Computer, Communication, Chemical, Material and Electronic Engineering
Country/TerritoryBangladesh
CityRajshahi
Period08/02/1809/02/18
Internet address

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