Amive: a computational infrastructure for autonomous and real-time identification and intervention for users with possible depressive profile in online social network

• Grant number: 20/05157-9
• Support Opportunities: Regular Research Grants
• Start date: April 01, 2021
• End date: September 30, 2023
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Agreement: MCTI/MC
• Principal Investigator: Vânia Paula de Almeida Neris
• Grantee: Vânia Paula de Almeida Neris
• Host Institution: Centro de Ciências Exatas e de Tecnologia (CCET). Universidade Federal de São Carlos (UFSCAR). São Carlos , SP, Brazil
• Associated researchers: Helena de Medeiros Caseli ; Hélio Crestana Guardia ; Heloisa Cristina Figueiredo Frizzo ; Jair Borges Barbosa Neto ; Larissa Campagna Martini Barbosa ; Luciano de Oliveira Neris ; Taís Bleicher ; Vânia Paula de Almeida Neris ; Vivian Genaro Motti
• Associated scholarship(s): 23/07943-0 - Design, implementation and testing of computational content for mental health promotion and prevention, BP.TT; 23/07862-0 - Psychosocial support for Amive project participants with identified psychological distress, BP.TT; 22/09173-4 - Amive: a computational infrastructure for autonomous and real-time identification and intervention of users with a possible depressive profile in an online social network, BP.TT; 22/07487-1 - Psychosocial support for Amive project participants with identified psychological distress, BP.TT; 22/07881-1 - Design, implementation and testing of computational content for mental health promotion and prevention, BP.TT

Abstract

Depression causes clinically significant suffering and/or impairment in the individual's social functioning. There is a consensus in the health care area that, in these cases, it is necessary to offer a comprehensive care model, not restricted to drugs. In this context, there are solutions that can support the diagnosis and interventions for people with a possible depressive profile (PPD), analyzing their behavior on the Internet, more specifically on Online Social Network (RSO). Current research adopts text analysis to try to identify people with PPD in RSO. However, PPDs can intentionally alter the text to generate a desired social impact. One of the scientific challenges of this project is to combine the textual analysis of posts in RSO with physiological signals and psychometric evaluation scales aiming at a more accurate identification of PPD. In addition to identification, it is understood that the interaction options offered in RSO could be explored as personalized channels of intervention by a computational solution capable of dialoguing with PPD. Thus, this project aims, through a quali-quanti research approach, to investigate a new computing solution for the Internet, which identifies Brazilian users with PPD and to provide and clinically test an autonomous, specialized and personalized intervention via RSO. This solution is as a computational infrastructure and presupposes the construction of a multifactorial model for the identification and an intervention model that explores beyond the text, other media that make sense in RSO as image and music. (AU)