论文标题
LT3在Semeval-2020任务9：跨语性的嵌入式情感分析的社交媒体文本
LT3 at SemEval-2020 Task 9: Cross-lingual Embeddings for Sentiment Analysis of Hinglish Social Media Text
论文作者
论文摘要
本文介绍了我们对代码混合社交媒体文本的情感分析对Semeval-2020任务9的贡献。我们研究了两种方法来解决Hinglish情感分析的任务。第一种方法使用在同一空间中投射出来的含Hinglish和预训练的英语FastText单词嵌入而产生的跨语性嵌入。第二种方法结合了预先训练的英语嵌入，这些嵌入方式通过一组Hinglish推文逐渐重新训练。结果表明，第二种方法的表现最佳，在固定测试数据中，F1得分为70.52％。
This paper describes our contribution to the SemEval-2020 Task 9 on Sentiment Analysis for Code-mixed Social Media Text. We investigated two approaches to solve the task of Hinglish sentiment analysis. The first approach uses cross-lingual embeddings resulting from projecting Hinglish and pre-trained English FastText word embeddings in the same space. The second approach incorporates pre-trained English embeddings that are incrementally retrained with a set of Hinglish tweets. The results show that the second approach performs best, with an F1-score of 70.52% on the held-out test data.
