Exploring Lavender Tongue from Social Media Texts

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 68 The 2017 Conference on Computational Linguistics and Speech Processing ROCLING 2017, pp. 68-80  The Association for Computational Linguistics and Chinese Language Processing