What's in a Name? -- Gender Classification of Names with Character Based Machine Learning Models
Gender information is no longer a mandatory input when registering for an account at many leading Internet companies. However, prediction of demographic information such as gender and age remains an important task, especially in intervention of unintentional gender/age bias in recommender systems. Therefore it is necessary to infer the gender of those users who did not to provide this information during registration. We consider the problem of predicting the gender of registered users based on their declared name. By analyzing the first names of 100M+ users, we found that genders can be very effectively classified using the composition of the name strings. We propose a number of character based machine learning models, and demonstrate that our models are able to infer the gender of users with much higher accuracy than baseline models. Moreover, we show that using the last names in addition to the first names improves classification performance further.
Code (0)
등록된 구현이 없습니다.
Tasks
BIG-bench Machine LearningGender ClassificationGeneral ClassificationRecommendation SystemsSimilar Papers 제목 키워드 기반
Gender Inference using Statistical Name Characteristics in Twitter
Much attention has been given to the task of gender inference of Twitter users. Although names are strong gender indicators, the names of Twitter users are rarely used as a feature; probably due to the high number of ill…
What Your Username Says About You
Usernames are ubiquitous on the Internet, and they are often suggestive of user demographics. This work looks at the degree to which gender and language can be inferred from a username alone by making use of unsupervised…
Beyond Binary Gender Labels: Revealing Gender Biases in LLMs through Gender-Neutral Name Predictions
Name-based gender prediction has traditionally categorized individuals as either female or male based on their names, using a binary classification system. That binary approach can be problematic in the cases of gender-n…
Binary ClassificationGender PredictionPredictionOn the Influence of Gender and Race in Romantic Relationship Prediction from Large Language Models
We study the presence of heteronormative biases and prejudice against interracial romantic relationships in large language models by performing controlled name-replacement experiments for the task of relationship predict…
Gender Prediction Based on Vietnamese Names with Machine Learning Techniques
As biological gender is one of the aspects of presenting individual human, much work has been done on gender classification based on people names. The proposals for English and Chinese languages are tremendous; still, th…
BIG-bench Machine LearningGender ClassificationGender PredictionText Classification