International Journal of Scientific Development and Research - IJSDR
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Paper Title: Mental Health Analysis using ABSA and Affective Computing
Authors Name: Ishani Koul , K Tarun Naidu , Harshitha B.S , Ayush Gupta , Dr. Dayananda R.B
Unique Id: IJSDR2008023
Published In: Volume 5 Issue 8, August-2020
Abstract: This study examines the relationship between facial and textual aspects and psychological characteristics of the user. The aim of the study was to find methods to detect depressivity of the user based on their facial expressions and textual scripts. Depression is a major affective disorder. The effects of depression extend beyond the individual patient, with negative impact on patients’ employers, spouses, and children. According to the World Health Organization, depression is the most common mental disorder. Currently, 300 million people suffer from depression and the numbers keep increasing. The prevalence of depression in the adult population (i.e., clinical depression and definite depression) has been reported at approximately 5% across cultures (Klimusová et al., 2016), and approximately 20% in its milder form (partial symptoms, mild depression, and probable depression (Cho et al., 1998). This paper aims to develop a multimodal system that can detect depression more accurately and can help the person to cope with the same. The application of Sentiment Analysis and Affective Computing are done for the same.
Keywords: Depression; Sentiment Analysis; Affective Computing; Multimodal; Facial recognition; Textual;
Cite Article: "Mental Health Analysis using ABSA and Affective Computing", International Journal of Science & Engineering Development Research (www.ijsdr.org), ISSN:2455-2631, Vol.5, Issue 8, page no.211 - 214, August-2020, Available :http://www.ijsdr.org/papers/IJSDR2008023.pdf
Downloads: 00060116
Publication Details: Published Paper ID: IJSDR2008023
Registration ID:192310
Published In: Volume 5 Issue 8, August-2020
DOI (Digital Object Identifier):
Page No: 211 - 214
Publisher: IJSDR | www.ijsdr.org
ISSN Number: 2455-2631

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