@inproceedings{2a0a565aa665482d8385134506f02e58,
title = "Sharing behavior in online social media: An empirical analysis with deep learning",
abstract = "We conduct a large-scale empirical study on the sharing behavior in social media to measure the effect of message features and initial messengers on information diffusion. Our analysis focuses on messages created by companies and utilizes both textual and visual semantic content by employing state-of-the-art machine learning methods: topic modeling and deep learning. We find that messages with multiple conspicuous images and messengers with similar content are crucial in the diffusion process. Our approach for semantic content analysis, particularly for visual content, bridges advanced machine learning techniques for effective marketing and social media strategies.",
keywords = "Community analysis, Deep learning, Information diffusion, Social media, Topic modeling",
author = "Donghyuk Shin and Shu He and Lee, {Gene Moo} and Whinston, {Andrew B.}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016. Copyright: Copyright 2017 Elsevier B.V., All rights reserved.; 15th Workshop on e-Business on E-Life: Web-Enabled Convergence of Commerce, Work, and Social Life, WEB 2015 ; Conference date: 12-12-2015 Through 12-12-2015",
year = "2016",
doi = "10.1007/978-3-319-45408-5_26",
language = "English (US)",
isbn = "9783319454078",
series = "Lecture Notes in Business Information Processing",
publisher = "Springer Verlag",
pages = "222--227",
editor = "Vijayan Sugumaran and Victoria Yoon and Shaw, {Michael J.}",
booktitle = "E-Life",
}