A General Gender Inference Method Based on Web
Hong Yan Yang, Yali Yuan · 2016
Gender information, as a crucial part of human demographics, is valuable for its abundant connotations and potential applications.Though much effort has been made on the problem of gender inference, most existing methods are highly dependent on data from specific sources, like Twitter, and are difficult to be generalized to other tasks.In this work, we propose a general Web-based method for gender inference.We show that our model significantly outperforms state-of-the-art without much human workload or any limits on specific scenarios.Based on that, we also present a voting framework to efficiently incorporate several methods to further improve performance.Experiments show that our voting framework can achieve 96.9% accuracy.