Hsiao-Han Wu

Under the issue of gender and Natural Language Processing (NLP), most papers aim at gendernorm language that spoken by biologically males and females with opposite-sex desires. However, from the point of view of sexual orientation, this study presents the first work in the task of Chinese homosexual identification. Firstly, we collect homosexual texts from social media, and secondly examine linguistic behavior found in gay and lesbian texts. In addition, we also provide sets of linguistic features to automatically predict homosexual language with the adoption of 5-fold cross-validation Support Vector Machine (SVM) and Naive Bayes (NB) models. Training procedure in the study resulted in promising f-score around 70% with the use of particular lexicon-based feature set.

This paper tries to demonstrate our exploratory efforts in tackling with the “high accuracy-low quantity” problem of human word sense annotation task in Chinese, and ultimately reach the goal of automatic word sense annotation. Our proposed annotation architecture consists of explicit and implicit aspects of of crowdsourcing approach. Explicit method focuses on the general issues of crowdsourcing and made adjustments on current MTurk framework. Implicit method concentrates on the idea of Game with a Purpose (GWAP) design, which originates from a well-known video game Super Mario.