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Internet is changing the landscape of journalism in the digital age, and now everyone can publish news contents on the Web. While it certainly brings speed and democracy, it also attracts money makers who create low-quality articles. Clickbait is a type of low-quality online articles that often includes exaggerated headlines with irrelevant contents. Recently, Prof. William Wang at UCSB Computer Science has received a gift award from Bytedance to work on an important problem of clickbait detection. The goal of this project is to design new semi-supervised learning algorithm to leverage unlabeled data and improve the accuracy of the machine learning system for clickbait detection.

Beijing Bytedance Technology Co., Ltd. is a tech company underpinned by AI and mobile Internet. Its flagship app “Toutiao”(which means “headline” in Chinese), one of the fastest growing mobile products in China, initiated personalized information flow, thereby creating a new way to connect people with information through massive information gathering, in-depth data mining and user behavior analysis. In addition, Bytedance continuously strides in video, Q&A, image and other fields, powered by a range of products including “Tik Tok/Douyin”, “Hypstar/Huoshan”, “Xigua Video”, “Neihan Duanzi”, “Wukong Q&A” and “Tuchong”. The company is currently valued at $20 billion.