Many people use social media in their daily life for entertainment, business, personal communication, and catching up with friends. In social media marketing, sentiment analysis is one of the most popular research topics because it can be employed to perform brand or market research monitoring and to keep an eye on the competitors. Machine learning algorithms have been utilized to carry out the task. In addition, sentiment analysis is essential in cognitive computing. Currently, there are still a limited number of Thai sentiment analysis research. This paper proposes a framework for sentiment analysis in Thai along with Thai-SenticNet5 corpus. The framework employs different types of features, namely, word embedding, part-of-speech, sentic features, and all combinations of these features. Furthermore, we fused deep learning algorithms—convolutional neural network (CNN) and bidirectional long short-term memory (BLSTM)—in different ways and compare it to several other fused combinations. Three datasets in Thai were used in this work: ThaiTales, ThaiEconTwitter, and Wisesight datasets. The experimental results show that combining all three features and fusing deep learning algorithms were able to improve overall performance. The best hybrid deep learning was BLSTM-CNN that achieved F₁-scores of 0.7436, 0.7707, and 0.5521, on ThaiTales, ThaiEconTwitter, and Wisesight datasets, respectively. According to the experimental results, we conclude that feature combination and hybrid deep learning algorithms can improve the overall performances.

许多人在日常生活中使用社交媒体进行娱乐，商务，个人交流和与朋友见面。在社交媒体营销中，情感分析是最受欢迎的研究主题之一，因为它可用于执行品牌或市场研究监控并密切关注竞争对手。机器学习算法已被用来执行任务。另外，情感分析在认知计算中是必不可少的。目前，泰国情绪分析研究仍然有限。本文与Thai-SenticNet5语料库一起为泰语中的情感分析提出了一个框架。该框架采用不同类型的功能，即单词嵌入，词性，感觉功能以及这些功能的所有组合。此外，我们以不同的方式融合了深度学习算法-卷积神经网络（CNN）和双向长短期记忆（BLSTM）-并将其与其他几种融合组合进行了比较。这项工作中使用了三种泰语数据集：ThaiTales，ThaiEconTwitter和Wisesight数据集。实验结果表明，将所有这三个功能结合在一起并融合深度学习算法可以提高整体性能。最好的混合深度学习是BLSTM-CNN 实验结果表明，将所有这三个功能结合在一起并融合深度学习算法可以提高整体性能。最好的混合深度学习是BLSTM-CNN 实验结果表明，将所有这三个功能结合在一起并融合深度学习算法可以提高整体性能。最好的混合深度学习是BLSTM-CNN在ThaiTales，ThaiEconTwitter和Wisesight数据集上的F ₁分数分别为0.7436、0.7707和0.5521。根据实验结果，我们得出结论，特征组合和混合深度学习算法可以提高整体性能。