Martin Mafunda
Biographic Data
| ID | 6027488 |
|---|---|
| NAME | Martin Mafunda |
| GIVEN NAMES | Martin |
| FAMILY NAME | Mafunda |
| SIGNATURE | MAFUNDA M |
| AFFILIATIONS | University of Johannesburg Johannesburg South Africa |
| ORCID | 0000-0001-9008-5834 |
| VERIFIED | Yes |
| TOTAL WORKS | 3 |
| TOTAL CITATIONS | 5 |
| AUTHOR COUNT | 3 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2023 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 1 |
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…
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 …
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 …
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 …
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 (2 works) · Artificial Intelligence (1 works) · Computational and Text Analysis Methods (1 works) · Computer Science (1 works) · Construct (python library (1 works) · Discourse analysis (1 works) · Divergence (linguistics) (1 works) · Group (periodic table) (1 works) · Hate Speech and Cyberbullying Detection (1 works) · Interpersonal ties (1 works)