Rapidly development of online social networks, millions of social media users like to upload or post or share their daily emotional experiences through text message, images and videos using different social media networks such as twitter, facebook. For the developing various applications the analysis of sentiments in social media users created images are increasingly important. Insufficient investigate has been carried out on the use of text data associate with the images uploaded or posted by the social users, sufficient investigate focusing on the designing of visual features, various conventional methods on image sentiment analysis are used. In this paper a novel approach which exploits latent correlation analysis of multi-views, we will works on sentiment analysis depends on visual and textual contents in social media. From textual and visual contents we were proposing hybrid approach of aggregating sentiments. In this proposed method we employing latent correlation analysis of multi-views (textual and image) to maximized latent correlations between multi-views.
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