紐約市有一個特別的聚會（meetup）文化，是由一群完全不認識的人，透過網路的連結，參加自己感興趣的聚會。其中，語言學習聚會是最受歡迎的聚會主題之一。來自不同文化背景和語言程度的學習者，定期聚在一起練習目標語言。由於紐約市聚會參與者的文化及語言多樣性，這些語言學習聚會的語料不僅為民族誌（ethnography）研究提供了豐富的研究基礎，還可用於第二語言習得、口語傳播和話語分析相關的研究。 然而，目前還沒有太多的研究聚焦於聚會脈絡下，性別在第二語言習得中所扮演的角色。社會語言學家長期以來一直研究性別在不同社會脈絡下，對於語言使用所造成的差異，而這些發現或假設是否適用於第二語言習得卻較少受到關注。本研究利用在中文／英文語言聚會所搜集的雙語資料：1）探討第二語言使用中的性別差異，包括詞頻、語碼轉換、目標語使用比例和情感等；2）建立一個計算模型，將這些假設作為特徵來預測說話者的性別。

New York City has a dynamic meetup culture where people gather for shared interests. Some of the most popular meetups are focused on language learning. Learners from diverse backgrounds and proficiency levels come together regularly to practice the target language(s). Due to the diversity of meetup participants and the multitude of languages spoken in New York City, these language meetups provide fertile research ground for linguistic research. However, there has been limited research regarding how gender plays a role in SLA within the context of meetup scenes. Sociolinguists have long studied gender differences in language use across various social contexts, but it remains unclear whether these findings or hypotheses are applicable to second language acquisition. Drawing upon transcribed bilingual data, this study aims to 1) explore gender differences in second language use, including word frequency, code-switching, ratio of target language use, sentiment, and emotions, and 2) build a computational model with these hypotheses as features to predict the gender of speakers.

聚會；性別；第二語言習得；機器學習

meetups; gender; second language acquisition; machine learning