• 主题
高级搜索  >
历史搜索 清空历史
首页> 外文会议>Conference on the North American Chapter of the Association for Computational Linguistics: Human Language Technologies >Good News or Bad News: Using Affect Control Theory to Analyze Readers' Reaction Towards News Articles
【24h】

Good News or Bad News: Using Affect Control Theory to Analyze Readers' Reaction Towards News Articles

机译：好消息或坏消息：利用影响控制理论分析读者对新闻文章的反应

获取原文
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

This paper proposes a novel approach to sentiment analysis that leverages work in sociology on symbolic interactionism. The proposed approach uses Affect Control Theory (ACT) to analyze readers' sentiment towards factual (objective) content and towards its entities (subject and object). ACT is a theory of affective reasoning that uses empirically derived equations to predict the sentiments and emotions that arise from events. This theory relies on several large lexicons of words with affective ratings in a three-dimensional space of evaluation, potency, and activity (EPA). The equations and lexicons of ACT were evaluated on a newly collected news-headlines corpus. ACT lexicon was expanded using a label propagation algorithm, resulting in 86,604 new words. The predicted emotions for each news headline was then computed using the augmented lexicon and ACT equations. The results had a precision of 82%, 79%, and 68% towards the event, the subject, and object, respectively. These results are significantly higher than those of standard sentiment analysis techniques.
机译：本文提出了一种对象征性互动主义的社会学工作的新颖情绪分析方法。该拟议的方法使用影响控制理论（法案）来分析读者对事实（客观）内容以及其实体（主题和对象）的情绪。行为是一种情感推理理论，它使用经验衍生的方程来预测事件产生的情绪和情绪。该理论依赖于具有情感评级的几种大型词汇，在评估，效力和活动（EPA）的三维空间中。在新收集的新闻标题语料库中评估了法案的等式和词汇。 ACT Lexicon使用标签传播算法扩展，导致86,604个新单词。然后使用增强的词典和动作方程来计算每个新闻标题的预测情绪。结果分别具有82％，79％和68％的精确性，朝向事件，主题和对象。这些结果显着高于标准情绪分析技术的结果。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号