TY - JOUR
T1 - The Mood of the Silver Economy: A Data Science Analysis of the Mood States of Older Adults and the Implications on their Wellbeing
AU - Palomino, M
AU - Allen, R
AU - Aider, F
AU - Tirotto, FA
AU - Giorgi, I
AU - Alexander, H
AU - Masala, G
PY - 2022/9/26
Y1 - 2022/9/26
N2 - For the first time in the history of humanity, the number of people over 65 surpassed those under 5 in 2018.
Undoubtedly, older people will play a significant role in the future of the economy and society in general, and technological innovation will be indispensable to support them. Thus, we were interested in learning how home automation could enable older people to live independently for longer. To better understand this, we held focus groups with UK senior citizens in 2021, and
we analyzed the data derived from them from the perspective of affective computing. We have trained a machine learning classifier capable of distinguishing moods commonly associated with older adults. We have identified depression, sadness and anger as the most prominent mood states conveyed in our focus groups. Our practical insights can aid the design of strategic
choices concerning the wellbeing of the ageing population.
AB - For the first time in the history of humanity, the number of people over 65 surpassed those under 5 in 2018.
Undoubtedly, older people will play a significant role in the future of the economy and society in general, and technological innovation will be indispensable to support them. Thus, we were interested in learning how home automation could enable older people to live independently for longer. To better understand this, we held focus groups with UK senior citizens in 2021, and
we analyzed the data derived from them from the perspective of affective computing. We have trained a machine learning classifier capable of distinguishing moods commonly associated with older adults. We have identified depression, sadness and anger as the most prominent mood states conveyed in our focus groups. Our practical insights can aid the design of strategic
choices concerning the wellbeing of the ageing population.
UR - https://pearl.plymouth.ac.uk/context/secam-research/article/2003/viewcontent/palomino_fedcsis_2022.pdf
U2 - 10.15439/2022f50
DO - 10.15439/2022f50
M3 - Conference proceedings published in a journal
SN - 2300-5963
VL - 0
JO - Communication Papers of the 17th Conference on Computer Science and Intelligence Systems
JF - Communication Papers of the 17th Conference on Computer Science and Intelligence Systems
IS - 0
T2 - 17th Conference on Computer Science and Intelligence Systems
Y2 - 4 September 2022 through 7 September 2022
ER -