Incorporating Hand-crafted Features in a Neural Network Model for Stance Detection on Microblog

What is it about?

Stance indicates the author's attitude towards a specific target in a publicly stated opinion. Analyzing user stances regarding a target provides opportunities for decision-making to various organizations. We introduce a method for stance detection that bridges the gap between traditional machine learning techniques and neural network-based deep learning approaches.

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Photo by Markus Spiske on Unsplash

Photo by Markus Spiske on Unsplash

Why is it important?

Recently, online users extensively communicate and express their significant opinions and response about various topics, issues, or entities through microblogging sites, especially Twitter. It provides numerous opportunities for various organizations. For example, the political parties may judge their position among the voters towards election or other policies. The company may get the information about their product acceptance. Therefore, stance detection helps to make the decision process easier.