Maria Schuld
Biographic Data
| ID | 4395625 |
|---|---|
| NAME | Maria Schuld |
| GIVEN NAMES | Maria |
| FAMILY NAME | Schuld |
| SIGNATURE | SCHULD M |
| AFFILIATIONS | University of Johannesburg |
| ORCID | 0000-0001-8626-168X |
| VERIFIED | Yes |
| TOTAL WORKS | 6 |
| TOTAL CITATIONS | 13 |
| WORKS AS AUTHOR | 6 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2013 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 2 |
How language divides
Polarization is typically conceptualized as increasing distance between opposing attitudes. We argue instead that it unfolds through asymmetries in the group‐differentiating power of opinion language. In public discourse, actors use distinctive linguistic repertoires to signal alignment, mark boundaries, and render opinion landscapes intelligible. Conventional attitude scales estimate the distributions of private belief but cannot capture how the…
Alignment and Differentiation
This study examines the interplay between language and social connectedness in forming opinion‐based groups on social media. Drawing on small‐world theory and social identity theory, we propose a dual‐layer approach that combines semantic and network analysis to investigate the dynamics of group formation on X/Twitter during the 2021 COVID‐19 vaccination campaign in South Africa. Our findings reveal a nuanced process of social sorting, where user…
The Covid-19 Information Void
The erosion of public trust in health information and government communication, particularly during crises like the Covid-19 pandemic, highlights a critical challenge in how health policies are transmitted and received. This study examines the dramatic shift in public sentiment toward Covid-19 vaccination in South Africa during 2021, a period that saw a decline from initial high acceptance to significant hesitancy. We argue that a process of soci…
Polarization on social media
When people share information and converse on social media, they create “echo chambers” through preferential attachment to like‐minded people and opinions they already support. A great deal of research uses interactional ties between people—created by retweeting and following—to identify and study polarization in social networks. Some of this work then uses language analysis to characterize the opinions and concerns of subcommunities in the netwo…
Speaker landscapes
We propose a new method that embeds speakers into a spatial representation according to the linguistic similarity of their contributions to a debate. Such "speaker landscapes" can be constructed quantitatively using word embeddings by annotating text corpora of speech samples by tokens representing the speakers. The way embeddings are constructed from predictive machine learning models means that speaker-tokens are placed closer together if they …
The Prevalence of Violence in Post-Conflict Societies
After war — so the common definition suggests — comes peace. Recent research, however, shows that post-conflict societies sometimes experience levels of violence comparable to those in times of civil war. What changes are the labels under which violence is recorded and discussed. Political, conflict-related violence between armed groups, the government and civilians becomes ‘ordinary crime’ after conflict is officially resolved. This article argu…
The Prevalence of Violence in Post-Conflict Societies
After war — so the common definition suggests — comes peace. Recent research, however, shows that post-conflict societies sometimes experience levels of violence comparable to those in times of civil war. What changes are the labels under which violence is recorded and discussed. Political, conflict-related violence between armed groups, the government and civilians becomes ‘ordinary crime’ after conflict is officially resolved. This article argu…
Speaker landscapes
We propose a new method that embeds speakers into a spatial representation according to the linguistic similarity of their contributions to a debate. Such "speaker landscapes" can be constructed quantitatively using word embeddings by annotating text corpora of speech samples by tokens representing the speakers. The way embeddings are constructed from predictive machine learning models means that speaker-tokens are placed closer together if they …
Polarization on social media
When people share information and converse on social media, they create “echo chambers” through preferential attachment to like‐minded people and opinions they already support. A great deal of research uses interactional ties between people—created by retweeting and following—to identify and study polarization in social networks. Some of this work then uses language analysis to characterize the opinions and concerns of subcommunities in the netwo…
The Prevalence of Violence in Post-Conflict Societies
After war — so the common definition suggests — comes peace. Recent research, however, shows that post-conflict societies sometimes experience levels of violence comparable to those in times of civil war. What changes are the labels under which violence is recorded and discussed. Political, conflict-related violence between armed groups, the government and civilians becomes ‘ordinary crime’ after conflict is officially resolved. This article argu…
Speaker landscapes
We propose a new method that embeds speakers into a spatial representation according to the linguistic similarity of their contributions to a debate. Such "speaker landscapes" can be constructed quantitatively using word embeddings by annotating text corpora of speech samples by tokens representing the speakers. The way embeddings are constructed from predictive machine learning models means that speaker-tokens are placed closer together if they …
The Covid-19 Information Void
The erosion of public trust in health information and government communication, particularly during crises like the Covid-19 pandemic, highlights a critical challenge in how health policies are transmitted and received. This study examines the dramatic shift in public sentiment toward Covid-19 vaccination in South Africa during 2021, a period that saw a decline from initial high acceptance to significant hesitancy. We argue that a process of soci…
Polarization on social media
When people share information and converse on social media, they create “echo chambers” through preferential attachment to like‐minded people and opinions they already support. A great deal of research uses interactional ties between people—created by retweeting and following—to identify and study polarization in social networks. Some of this work then uses language analysis to characterize the opinions and concerns of subcommunities in the netwo…
How language divides
Polarization is typically conceptualized as increasing distance between opposing attitudes. We argue instead that it unfolds through asymmetries in the group‐differentiating power of opinion language. In public discourse, actors use distinctive linguistic repertoires to signal alignment, mark boundaries, and render opinion landscapes intelligible. Conventional attitude scales estimate the distributions of private belief but cannot capture how the…
Alignment and Differentiation
This study examines the interplay between language and social connectedness in forming opinion‐based groups on social media. Drawing on small‐world theory and social identity theory, we propose a dual‐layer approach that combines semantic and network analysis to investigate the dynamics of group formation on X/Twitter during the 2021 COVID‐19 vaccination campaign in South Africa. Our findings reveal a nuanced process of social sorting, where user…
Misinformation and Its Impacts (4 works) · Politics (3 works) · Law (2 works) · Law (2 works) · Opinion Dynamics and Social Influence (2 works) · Political science (2 works) · Social media (2 works) · Sociology (2 works) · Armed conflict (1 work) · Artificial Intelligence (1 work)