A visualization tool for interest analysis via emotion detection
Today, most personalized and recommendation services are built around interest extraction models but the outputs of these algorithms are ambiguous in nature. This makes it difficult to understand what users are personally interested in and more importantly what they are feeling towards these interests and how their interests transition through time. By studying both users' interests and emotions, simultaneously, one can further investigate the motivation behind these interests. Such findings can be useful to build better interest extraction models and algorithms that leverage personalized and recommendation services (e.g., ads. targeting, e-commerce and dating sites). In this paper, we propose the demonstration of a web visualization tool - EmoViz - which facilitates the further exploration of users' interests and their emotions at a global scale. Such tool, through the use of various visual components, aims to alleviate the problem of understanding what users of the world are interested in and the motivations behind their interests and feelings.
- Build real-time capabilities
- Timeline needs more adjusting capabilites.
- Dynamic Word Cloud
- Larger dataset
- Backend (API) connected with Twitter API.
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