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Stories can have tremendous power – not only useful for entertainment, they can activate our interests and mobilize our actions. The degree to which a story resonates with its audience may be in part reflected in the emotional journey it takes the audience upon. In this paper, we use machine learning methods to construct emotional arcs in movies, calculate families of arcs, and demonstrate the ability...
Visual sentiment analysis framework can predictthe sentiment of an image by analyzing the image contents. Nowadays, people are uploading millions of images in socialnetworks such as Twitter, Facebook, Google Plus, and Flickr. These images play a crucial part in expressing emotions of users in online social networks. As a result, image sentiment analysishas become important in the area of online multimedia...
Recent years have witnessed a rapid spread of multi-modality microblogs like Twitter and Sina Weibo composed of image, text and emoticon. Visual sentiment prediction of such microblog based social media has recently attracted ever-increasing research focus with broad application prospect. In this paper, we give a systematic review of the recent advances and cutting-edge techniques for visual sentiment...
Sentiment analysis is important for understanding the social media contents and user opinions. Along with the development of social media applications, an increasing number of people combine texts and images to express their opinions. However, text based sentiment analysis methods cannot process other medias except texts. Therefore, visual sentiment analysis is born at the right moment. In this article,...
In this paper we introduce the novel problem of understanding visual persuasion. Modern mass media make extensive use of images to persuade people to make commercial and political decisions. These effects and techniques are widely studied in the social sciences, but behavioral studies do not scale to massive datasets. Computer vision has made great strides in building syntactical representations of...
Today, online stores collect a lot of customer feedback in the form of surveys, reviews, and comments. This feedback is categorized and in some cases responded to, but in general it is underutilized - even though customer satisfaction is essential to the success of their business. In this paper, we introduce several new techniques to interactively analyze customer comments and ratings to determine...
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