Document Type

Thesis

Degree Name

Master of Arts (MA)

Department

Psychology

Program Name/Specialization

Community Psychology

Faculty/School

Faculty of Science

First Advisor

Ketan Shankardass

Advisor Role

Supervisor

Abstract

This study investigated stress and resilience at the neighbourhood level in Hamilton Ontario in pre- and peri-pandemic conditions using a social media analysis. Sentiment analysis of geo-located Twitter posts produced within Hamilton census tract boundaries was conducted using Stresscapes and EMOTIVE, validated software that extract and code emotional information from human language expressions about stress and hope (a proxy for stress), respectively. Baseline levels of both emotions were measured using aggregate scores at the census tract level in Hamilton from tweets produced during two pre-pandemic periods (March 2019 to July 2019; and August 2019 to February 2020), with a replication analysis corresponding to the first (March - July 2020), second (August 2020 - February 2021) and third (March 2021-July 2021) waves of the pandemic. The spatial distribution of stress and hope across the five time periods (pre- and peri-pandemic) was visualized using a geographic information system. Candidate explanatory variables (including COVID-19 cases count, visible minority status, educational attainment, household income, and household size) were examined for significant bivariate correlations with the change in stress emotions within neighbourhoods across pre- and peri-pandemic periods. Baseline hope was examined as an effect modifier of any significant relationships between explanatory variables and stress. Results suggest that variation between stress and hope emotions exist between Hamilton census tracts (n=30) over the five time periods. Among the explanatory variables, household size and household income displayed a strong bivariate correlation to stress; however, baseline hope did not modify the effect on stress of either variable.

Convocation Year

2022

Convocation Season

Spring

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