The handbook of language and gender

By Janet Holmes, M. Meyerhoff. 2003

Subfields: Evaluation & Benchmarks

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Evaluation & Benchmarks

1. Matteo Negri
2. Marco Turchi
3. Yupei Du
4. Svitlana Volkova
5. Man Lan
6. Paolo Rosso
7. Benno Stein
8. Dong Nguyen

Citations in the corpus

• Man is to Computer Programmer as Woman is to Homemaker? Debiasing Word Embeddings (2016, background): “, [13]) and we only highlight some of the findings here.”
• Word embeddings quantify 100 years of gender and ethnic stereotypes (2017, methodology): “Language analysis is a standard tool used to discover, understand, and demonstrate such stereotypes (Hamilton and Trolier, 1986; Basow, 1992; Wetherell and Potter, 1992; Holmes and Meyerhoff, 2008; Coates, 2015).”
• "How Old Do You Think I Am?" A Study of Language and Age in Twitter (2013, background): “From a sociolinguistic perspective, language is a resource which can be drawn on to study different aspects of a person’s social identity at different points in an interaction (Holmes and Meyerhoff 2003).”
• Overview of the 3rd Author Profiling Task at PAN 2015 (2015, result): “Similar research was done by the authors in [26, 8].”
• Computational Sociolinguistics: A Survey (2016, background): “, gender, age, ethnicity, status) and language use [62, 64, 120, 262].”
• Why Gender and Age Prediction from Tweets is Hard: Lessons from a Crowdsourcing Experiment (2014, background): “While historically gender has been treated as binary, researchers in fields such as sociology (Lorber, 1996) and sociolinguistics (Holmes and Meyerhoff, 2003; Bergvall et al., 1996) find this view too limited.”
• Discovering and Categorising Language Biases in Reddit (2020, background): “Linguistic biases have been the focus of language analysis for quite some time (Wetherell and Potter 1992; Holmes and Meyerhoff 2008; Garg et al. 2018; Bhatia 2017).”
• Exploring Demographic Language Variations to Improve Multilingual Sentiment Analysis in Social Media (2013, background): “Sociolinguistics and dialectology have been studying the relationships between language and speech at the phonological, lexical and morphosyntactic levels and social identity for decades (Picard, 1997; Gefen and Ridings, 2005; Holmes and Meyerhoff, 2004; Macaulay, 2006; Tagliamonte, 2006).”
• Gender Bias in Machine Translation (2021, background): “In this light, the study of gender and language variation has received much attention in socio- and corpus linguistics (Holmes and Meyerhoff, 2003; Eckert and McConnell-Ginet, 2013).”