Collective user behavior analysis for social intelligence

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The focus of this research and development project is on life event mentions on social media. Our work will**focus primarily on aspects that relate to life event prediction. While a large body of research has focused on**multimedia content such as images and videos to automatically retell a series of life events, little work has been**done on streaming textual content in online social networks for the purposes of life event prediction. This task**is challenging due to the short, informal and noisy characteristics of social media posts such as tweets. Further**and more importantly, the task also suffers from the "sparsity problem," as social media is dominated by**information other than life events. Research in this area has effectively used various types of features including**social interaction, syntactic, semantic, and neural embeddings to train classifiers with reasonable performance.**The objective of this project will be to work in close collaboration with ThinkCX, the industrial partner, and to**develop a multidimensional framework for exploring how life events can be predicted based on streaming**social textual content. This will enable the industrial partner to build tools that gain deeper insight into the**users' preferences and interests based on their life events, resulting in higher customer satisfaction and**customer engagement. The outcomes of this project will enable the industry partner to fine-tune its**understanding of the end-users and hence potentially increase its customer base, leading to growth in revenue**and the hiring of more employees in Canada.