Abstract
Existing micro-blog sentiment analysis basically calculates sentiment values from explicit features, but the hidden sentiment in text often have an important influence on the judgment of sentiment preference, a new sentiment analysis method is proposed here. First, the dynamic micro-blog data are collected and pretreated by combining Weibo crawlers and Web API. According to the characteristics of micro-blog to construct an emoji dictionary. Then, the semantic similarity and tendentiousness are calculated based on the extraction and classification of sentiment words of ConceptNet. Finally, the emoticons and the weight of marked emotion commonsense are used to calculate the sentiment preference value of the whole micro-blog text, which makes the judgment of the sentiment polarity more accurate. Experimental results show the effectiveness of this method.
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Acknowledgement
This Research work was supported in part by 2018 Cultivation Project of Top Talent in Anhui Colleges and Universities (Grant No. gxbjZD15), in part by 2019 Anhui Provincial Natural Science Foundation Project (Grant No. 1908085MF189).
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Xu, X., Zhang, S. (2021). Micro-blog Sentiment Analysis Based on Emoticon Preferences and Emotion Commonsense. In: Abawajy, J., Choo, KK., Xu, Z., Atiquzzaman, M. (eds) 2020 International Conference on Applications and Techniques in Cyber Intelligence. ATCI 2020. Advances in Intelligent Systems and Computing, vol 1244. Springer, Cham. https://doi.org/10.1007/978-3-030-53980-1_123
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DOI: https://doi.org/10.1007/978-3-030-53980-1_123
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