论文标题
Twitter情感分析的LSTM模型
An LSTM model for Twitter Sentiment Analysis
论文作者
论文摘要
在Twitter等社交媒体上的情感分析为组织和个人提供了一种有效的方式来监控对他们及其竞争对手的情感。结果，情感分析已成为一项重要且具有挑战性的任务。在这项工作中，我们收集了七个公开可用的，并手动注释的Twitter情感数据集。我们从收集的数据集中创建一个新的培训和测试数据集。我们开发了一个LSTM模型来对推文进行分类并使用新数据集评估模型。
Sentiment analysis on social media such as Twitter provides organizations and individuals an effective way to monitor public emotions towards them and their competitors. As a result, sentiment analysis has become an important and challenging task. In this work, we have collected seven publicly available and manually annotated twitter sentiment datasets. We create a new training and testing dataset from the collected datasets. We develop an LSTM model to classify sentiment of a tweet and evaluate the model with the new dataset.
