Name
Abstract | ||
|---|---|---|
Social identities carry widely agreed upon meanings, called stereotypes, that have important effects on social processes. In the present work, we develop a method to extract the stereotypes of Twitter users. Our method is grounded in two distinct strands of theory, one that represents stereotypes as identities' affective meanings and the other that represents stereotypes as semantic relationships between identities. After validating our approach via a prediction task, we apply the model to a dataset of 45 thousand Twitter users who actively tweeted about the Michael Brown and Eric Garner tragedies. Our work provides unique insights into the stereotypes of these users, as well as providing a way of quantifying stereotypes that blends existing sociological and psychological theory in a novel, parsimonious way. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1145/2998181.2998187 | CSCW |
Keywords | Field | DocType |
computational social science, social psychology, identity, stereotype, Twitter | Social psychology,Social identity theory,Psychology,Computational sociology,Social processes,Stereotype,Affect (psychology),Psychological Theory | Conference |
Citations | PageRank | References |
1 | 0.36 | 27 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kenneth Joseph | 1 | 70 | 9.46 |
| Wei Wei | 2 | 201 | 16.60 |
| Kathleen M. Carley | 3 | 2507 | 270.10 |