Publication | Closed Access
Detecting Depression Using K-Nearest Neighbors (KNN) Classification Technique
101
Citations
10
References
2018
Year
Social Data AnalysisEngineeringNetwork AnalysisCommunicationMultimodal Sentiment AnalysisClassification TechniqueComputational Social ScienceClassification MethodSocial MediaData ScienceData MiningPattern RecognitionMood SymptomAffective ComputingSocial Network AnalysisSocial Medium MiningSocial Network DataSocial NetworksDepression ProblemsPsychiatryKnowledge DiscoveryDepressionMental Health MonitoringNetwork ScienceSocial ComputingSocial Medium DataArtsPsychopathology
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.
| Year | Citations | |
|---|---|---|
Page 1
Page 1