https://scholars.lib.ntu.edu.tw/handle/123456789/577594
標題: | Exploring lavender tongue from social media texts | 作者: | Wu H.-H SHU-KAI HSIEH |
關鍵字: | Barium compounds; Computational linguistics; Natural language processing systems; Speech processing; Support vector machines; Cross validation; Feature sets; Lexicon-based; Linguistic features; NAtural language processing; Sexual orientations; Social media; Training procedures; Social networking (online) | 公開日期: | 2017 | 起(迄)頁: | 68-80 | 來源出版物: | Proceedings of the 29th Conference on Computational Linguistics and Speech Processing, ROCLING 2017 | 摘要: | Under the issue of gender and Natural Language Processing (NLP), most papers aim at gender-norm 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. ? The Association for Computational Linguistics and Chinese Language Processing |
URI: | https://www.scopus.com/inward/record.uri?eid=2-s2.0-85085912649&partnerID=40&md5=e40f7ad95a29d6484adf34e75cf93da7 https://scholars.lib.ntu.edu.tw/handle/123456789/577594 |
顯示於: | 語言學研究所 |
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