Multimodal image popularity prediction on social media

Journal of Computer Engineering & Information Technology.ISSN : 2324-9307

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Multimodal image popularity prediction on social media

Kai Lung Hua

National Taiwan University of Science and Technology, Taiwan

: J Comput Eng Inf Technol


Social media websites are one of the most important channels for content sharing and communication between users on social networks. The posted images on the websites, even the ones from the identical user, generally obtain very different numbers of views. This motivates researchers to predict the popularity of a candidate image on social media. To address this task, we investigate the effects of multimodal on user profile, post metadata, and photo aesthetics. The proposed method is evaluated via a large number of real image posts from Flickr. The experimental results verified the effectiveness of the proposed method. Recent Publications: 1. Xiaoou Tang, Wei Luo, and Xiaogang Wang (2013) Content-Based Photo Quality Assessment. IEEE Transactions on Multimedia 15(8):1930–1943.


Kai Lung Hua received the BS degree in Electrical Engineering from National Tsing Hua University in 2000, and the MS degree in Communication Engineering from National Chiao Tung University in 2002, both in Hsinchu, Taiwan. He received the PhD degree from the School of Electrical and Computer Engineering, Purdue University, West Lafayette, IN, in 2010. Since 2010, he has been with National Taiwan University of Science and Technology, where he is currently an Associate Professor in the Department of Computer Science and Information Engineering. He is a member of Eta Kappa Nu and Phi Tau Phi, as well as a recipient of MediaTek Doctoral Fellowship. His current research interests include digital image and video processing, computer vision, and multimedia networking. He has received several research awards, including Top 10% Paper Award of 2015 IEEE International Workshop on Multimedia Signal Processing, the Second Award of the 2014 ACM Multimedia Grand Challenge, the Best Paper Award of the 2013 IEEE International Symposium on Consumer Electronics, and the Best Poster Paper Award of the 2012 International Conference on 3D Systems and Applications.


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