计算机科学 ›› 2022, Vol. 49 ›› Issue (8): 279-293.doi: 10.11896/jsjkx.220300099
王剑1, 彭雨琦2, 赵宇斐2, 杨健3
WANG Jian1, PENG Yu-qi2, ZHAO Yu-fei2, YANG Jian3
摘要： 随着社交媒体平台的快速发展,舆情信息得以在极短的时间内大范围传播,如果不对舆情信息加以管理和控制,将对网络环境乃至社会环境造成巨大威胁。信息抽取技术因其语义化和精准性成为舆情分析和管理的第一步,也是最关键的一步。近年来,随着深度学习的发展,其自动学习潜在特征、组合特征的能力使信息抽取各个子任务的准确率都得到了很大的提高。文中结合社交网络舆情的特点和深度学习技术在信息抽取领域的应用,对基于深度学习的社交网络舆情信息抽取方法进行了系统的梳理和总结。首先整理了社交网络舆情信息的组织方式,详细阐述了舆情信息抽取的框架、评价指标,然后对现有的基于深度学习的舆情信息抽取模型进行了全面的回顾和分析,讨论了现有方法的适用性及局限性,最后对未来的研究趋势进行了展望。
中图分类号:
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