Name
Abstract | ||
|---|---|---|
•Inferential analytics may reinforce existing biases about gender stereotyping.•In a N = 109 pilot sample, 19% of Twitter users were misgendered.•Gender classifiers are binary and do not account for other than male/female gender categories.•LGBTQAI+ community members and straight women may be more often misgendered than straight men in social media. |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1016/j.ipm.2021.102541 | Information Processing & Management |
Keywords | DocType | Volume |
Gender,Twitter,Social media,Inference,Gender classifier,Automated gender recognition system,Privacy,Algorithmic bias,Discrimination,LGBTQAI+,Gender stereotyping,Online Behavioral Advertising | Journal | 58 |
Issue | ISSN | Citations |
3 | 0306-4573 | 2 |
PageRank | References | Authors |
0.38 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Eduard Fosch Villaronga | 1 | 22 | 9.03 |
| A. Poulsen | 2 | 2 | 0.38 |
| R.A. Søraa | 3 | 2 | 0.38 |
| B.H.M. Custers | 4 | 2 | 0.38 |