Gender Classification of Chinese Weibo Users
Yao Yu, Tianfang Yao · 2017
User profiles describe users with many personalized features, which help us recognize and understand users. Gender classification is one of the fundamental research tasks on user profiles. Recently there are few studies on gender classification of Chinese micro-blog authors. In this paper we present an efficient gender classification model to predict the gender values of specified users crawled from Sina Weibo, a Chinese micro-blog service. We also discuss the difference between several classification models and algorithms, then try to optimize our solutions. Finally, we present the experimental results and examine the behavior and scalability of our model, and validate our approach by examining different classifiers over a large dataset.