Micro-blog emotion prediction method based on weak supervised type multi-modal deep learning

Abstract

The invention discloses a micro-blog emotion prediction method based on weak supervised type multi-modal deep learning and relates to the field of multi-modal emotion analysis. The method comprises the following steps of preprocessing micro-blog multi-modal data; carrying out the weak supervised training of a multi-modal deep learning model; and carrying out the micro-blog emotion prediction of the multi-modal deep learning model. The method solves the problems of the multi-modal discriminant expression and the data label limitation existing in the emotion prediction of the micro-blog multi-channel content in the prior art, and realizes the final multi-modal emotion class prediction, wherein the accuracy is adopted as the experiment evaluation standard. The consistency degree between the predicted micro-blog emotion polarity category and the pre-marked emotion category is reflected. The performance of the method is greatly improved and the correlation among multiple modals is considered. As a result, an optimal effect is achieved in the aspect of the overall multi-modal performance. An ideal classification effect is achieved for different emotion categories. Through the weak supervised training, an initial model for text and image modals is obviously improved in the aspect of emotion classification effect.

Description

technical field [0001] The invention relates to the field of multimodal sentiment analysis, in particular to a microblog sentiment prediction method based on weakly supervised multimodal deep learning. Background technique [0002] Recently, with the rapid development of large social platforms such as Sina Weibo, the scale of multimedia data in social networks is increasing every day. Taking Sina Weibo as an example, as of March 2016, the monthly active users of Sina Weibo reached 260 million. As one of the most popular platforms, Sina Weibo enables Internet users to express their emotions on topics of interest to them. Therefore, it has attracted a large amount of research on emotional information mining, which involves some emerging applications including event detection, social network analysis, and business recommendation. [0003] An obvious feature of the development of Weibo is the growth of multimodal information, such as images, videos, short texts, and rich emotic...

AI Technical Summary

Problems solved by technology

[0006] The purpose of the present invention is to provide a microblog based on weakly supervised multimodal deep learning for the problem of multimodal discriminant representation and limited data labels in the emotion prediction on microblog multi-channel content (multimodal). Sentiment Prediction Methods

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