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.
翻译:对Twitter等社交媒体的感官分析为各组织和个人提供了一种有效的方式来监测公众对他们及其竞争对手的情绪。结果,情绪分析成为一项重要而具有挑战性的任务。在这项工作中,我们收集了7个公开的、手动附加注释的Twitter情绪数据集。我们从所收集的数据集中创建了新的培训和测试数据集。我们开发了一个LSTM模型,对推特的情绪进行分类,并用新的数据集对模型进行评估。