TY - GEN
T1 - COVID-19 and Mental Health/Substance Use Disorders on Reddit
T2 - 25th International Conference on Pattern Recognition Workshops, ICPR 2020
AU - Alambo, Amanuel
AU - Padhee, Swati
AU - Banerjee, Tanvi
AU - Thirunarayan, Krishnaprasad
N1 - Publisher Copyright:
© Springer Nature Switzerland AG 2021.
PY - 2021
Y1 - 2021
N2 - COVID-19 pandemic has adversely and disproportionately impacted people suffering from mental health issues and substance use problems. This has been exacerbated by social isolation during the pandemic and the social stigma associated with mental health and substance use disorders, making people reluctant to share their struggles and seek help. Due to the anonymity and privacy they provide, social media emerged as a convenient medium for people to share their experiences about their day to day struggles. Reddit is a well-recognized social media platform that provides focused and structured forums called subreddits, that users subscribe to and discuss their experiences with others. Temporal assessment of the topical correlation between social media postings about mental health/substance use and postings about Coronavirus is crucial to better understand public sentiment on the pandemic and its evolving impact, especially related to vulnerable populations. In this study, we conduct a longitudinal topical analysis of postings between subreddits r/depression, r/Anxiety, r/SuicideWatch, and r/Coronavirus, and postings between subreddits r/opiates, r/OpiatesRecovery, r/addiction, and r/Coronavirus from January 2020–October 2020. Our results show a high topical correlation between postings in r/depression and r/Coronavirus in September 2020. Further, the topical correlation between postings on substance use disorders and Coronavirus fluctuates, showing the highest correlation in August 2020. By monitoring these trends from platforms such as Reddit, epidemiologists, and mental health professionals can gain insights into the challenges faced by communities for targeted interventions.
AB - COVID-19 pandemic has adversely and disproportionately impacted people suffering from mental health issues and substance use problems. This has been exacerbated by social isolation during the pandemic and the social stigma associated with mental health and substance use disorders, making people reluctant to share their struggles and seek help. Due to the anonymity and privacy they provide, social media emerged as a convenient medium for people to share their experiences about their day to day struggles. Reddit is a well-recognized social media platform that provides focused and structured forums called subreddits, that users subscribe to and discuss their experiences with others. Temporal assessment of the topical correlation between social media postings about mental health/substance use and postings about Coronavirus is crucial to better understand public sentiment on the pandemic and its evolving impact, especially related to vulnerable populations. In this study, we conduct a longitudinal topical analysis of postings between subreddits r/depression, r/Anxiety, r/SuicideWatch, and r/Coronavirus, and postings between subreddits r/opiates, r/OpiatesRecovery, r/addiction, and r/Coronavirus from January 2020–October 2020. Our results show a high topical correlation between postings in r/depression and r/Coronavirus in September 2020. Further, the topical correlation between postings on substance use disorders and Coronavirus fluctuates, showing the highest correlation in August 2020. By monitoring these trends from platforms such as Reddit, epidemiologists, and mental health professionals can gain insights into the challenges faced by communities for targeted interventions.
KW - COVID-19
KW - Longitudinal study
KW - Mental health
KW - Reddit
KW - Substance use
KW - Topic modeling
KW - Topical correlation
UR - http://www.scopus.com/inward/record.url?scp=85110736050&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85110736050&partnerID=8YFLogxK
UR - https://corescholar.libraries.wright.edu/cse/635
U2 - 10.1007/978-3-030-68790-8_2
DO - 10.1007/978-3-030-68790-8_2
M3 - Conference contribution
AN - SCOPUS:85110736050
SN - 9783030687892
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 20
EP - 27
BT - Pattern Recognition
A2 - Del Bimbo, Alberto
A2 - Bertini, Marco
A2 - Sclaroff, Stan
A2 - Mei, Tao
A2 - Escalante, Hugo Jair
A2 - Cucchiara, Rita
A2 - Vezzani, Roberto
A2 - Farinella, Giovanni Maria
PB - Springer Science and Business Media Deutschland GmbH
Y2 - 10 January 2021 through 15 January 2021
ER -