Michal Monselise

Michal Monselise

PhD Candidate at Drexel University

Publications

Topics and Sentiments of Public Concerns Regarding COVID-19 Vaccines: Social Media Trend Analysis

Published in Journal of Internet Medical Research, 2021

The goal of this research is to understand public sentiment towards COVID-19 vaccines by analyzing discussions about the vaccines on social media for a period of sixty days when the vaccines were started in US. Using the combination of topic detection and sentiment analysis, we identify different types of concerns regarding vaccines that are expressed by different groups of the public that appear in social media.

Recommended citation: Monselise M, Chang C, Ferreira G, Yang R, Yang CC, Topics and Sentiments of Public Concerns Regarding COVID-19 Vaccines: Social Media Trend Analysis, Journal of Medical Internet Research. https://preprints.jmir.org/preprint/30765

Information Exchange in Online Health Communities Discussing COVID-19

Published in IEEE ICHI, 2021

As the COVID-19 pandemic spread through the United States, many people were left with questions regarding this novel disease. When few reliable sources were available, many turned to social media for information. Individuals reached out to online health communities to learn more about many aspects of the condition like symptoms, treatments, prognosis, and management of the disease. This study examines the informational exchange between users in an online health community during the first three months of the lockdown in the United States. Using social network analysis, we aim to characterize the informational exchange between users in a number of topics. Due to COVID-19 being a novel health condition, we observe only informational exchanges between users. Information seeking topics identified in the data were public health practice and psychological impacts, symptoms, health risk, transmission, management, prognosis, prevention, and protocol. We form a graph for each type of information seeking exchange. We use different metrics extracted from each information seeking graph to characterize the interaction between the users. Using these metrics, we can provide insight on how each type of information seeking differs for users of COVID-19 related online health communities as well as how social media networks can better serve their users in times of health uncertainty.

Recommended citation: M. Monselise and C. C. Yang, “Information Exchange in Online Health Communities Discussing COVID-19,” Proceedings of IEEE International Conference on Healthcare Informatics 2021,, Victoria, BC, Canada, August 9 – 12, 2021. http://www.ischool.drexel.edu/faculty/cyang/pub-c.html

Understanding the Social Support Exchange of a Pregnancy After Loss Online Support Group

Published in IEEE ICHI, 2020

Existing literature on miscarriage support seldom focuses on women who are pregnant after a loss despite research showing that these women have different social support needs from the general population of women who have suffered a loss. In light of this, we investigated an online support group for women who are pregnant after suffering a previous pregnancy loss in this study. The study utilized social network analysis to analyze the interactions between women of different gestational stages. We distinguish between the two types of social support exchanged in the group: informational and nurturant support. The graph structure allows us to learn about the progression of giving and receiving support as users progress through the gestational stages. Our study shows that informational support is mostly given by women in the later stages of their pregnancy to women in earlier stages. Most of the gestational stages only transmit or receive informational support but not both. Emotional support contains more reciprocal relationships between the gestational stages. We also aim to learn about the support exchanged in the group by analyzing the n-cliques formed in the group. We discuss how the findings of this research point to the importance of second trimester users in the group. We identify second trimester users that tend to spur more discussion in the group by interacting with more users, posting more messages, and having higher degree centrality.

Recommended citation: M. Monselise and C. C. Yang, “Understanding the Social Support Exchange of a Pregnancy After Loss Online Support Group,” Proceedings of IEEE International Conference on Healthcare Informatics 2020, Oldenburg, Germany, November 30 – December 3, 2020. https://ieeexplore.ieee.org/document/9374389