TY - GEN
T1 - Social and Web Data Framework for Understanding Loneliness
AU - Shah, Hurmat Ali
AU - Househ, Mowafa
N1 - Publisher Copyright:
© 2024 The Authors.
PY - 2024/8/22
Y1 - 2024/8/22
N2 - Loneliness can be studied through social media and web data to gain insights into the dynamic phenomenon. In this paper, we present our proposed framework through a case study on how to deploy various social media and online data sources to study loneliness comprehensively. The framework is important to understand loneliness from data perspective available online and to complement the theoretical and psychosocial understanding of loneliness. The data on loneliness is gathered through surveys and self-reporting mechanisms. This requires complementing the dynamic and vast data available on the web and through social media. Our results found that tools like Google Trend and News Analysis can give the starting point to explore loneliness in a particular region. Tools like X (formerly Twitter), Reddit, and other social media can give behavioral data on loneliness which can be analyzed through sentiment analysis and other social intelligence analysis. The framework's utility lies in its potential to inform policies, interventions, and initiatives addressing loneliness through data. However, it is crucial to acknowledge limitations, such as data availability, biases in user-generated content, and ethical considerations.
AB - Loneliness can be studied through social media and web data to gain insights into the dynamic phenomenon. In this paper, we present our proposed framework through a case study on how to deploy various social media and online data sources to study loneliness comprehensively. The framework is important to understand loneliness from data perspective available online and to complement the theoretical and psychosocial understanding of loneliness. The data on loneliness is gathered through surveys and self-reporting mechanisms. This requires complementing the dynamic and vast data available on the web and through social media. Our results found that tools like Google Trend and News Analysis can give the starting point to explore loneliness in a particular region. Tools like X (formerly Twitter), Reddit, and other social media can give behavioral data on loneliness which can be analyzed through sentiment analysis and other social intelligence analysis. The framework's utility lies in its potential to inform policies, interventions, and initiatives addressing loneliness through data. However, it is crucial to acknowledge limitations, such as data availability, biases in user-generated content, and ethical considerations.
KW - Social media
KW - loneliness
KW - social intelligence analysis
UR - https://www.scopus.com/pages/publications/85202007009
U2 - 10.3233/SHTI240333
DO - 10.3233/SHTI240333
M3 - Conference contribution
C2 - 39176662
AN - SCOPUS:85202007009
T3 - Studies in Health Technology and Informatics
SP - 14
EP - 18
BT - Digital Health and Informatics Innovations for Sustainable Health Care Systems - Proceedings of MIE 2024
A2 - Mantas, John
A2 - Hasman, Arie
A2 - Demiris, George
A2 - Saranto, Kaija
A2 - Marschollek, Michael
A2 - Arvanitis, Theodoros N.
A2 - Ognjanovic, Ivana
A2 - Benis, Arriel
A2 - Gallos, Parisis
A2 - Zoulias, Emmanouil
A2 - Andrikopoulou, Elisavet
PB - IOS Press BV
T2 - 34th Medical Informatics Europe Conference, MIE 2024
Y2 - 25 August 2024 through 29 August 2024
ER -