一种基于词序的社会情感演变分析模型

BTMESE:a bigram topic model for analyzing the evolution of social emotions

提出了一种基于词序的社会情感演变分析模型(BTMESE),模型通过引入文档中词与词之间的前后关联性,以期有效地揭示时间、文本、情感三种信息之间的潜在联系,进而追踪社会情感演变趋势,进一步提高情感分析的准确率。该模型可应用于情感预测、时间预测等领域。通过在真实世界的数据集上进行验证,结果证明该模型简单有效,能够较好地进行社会情感分析。

We introduce a novel bigram topic model for analyzing the evolution of social emotions （BTMESE）. Specifically, the proposed model can discern the semantic relationships among time, texts, and social emotions by creatively integrating word-order information. In particular, the model could be applied to a wide range of application scenarios, such as emotion prediction and time prediction. The ex- periments based on real world datasets validate the model＇s effectiveness in terms of social emotion analysis.