  Social media can be a double-edged sword for society, either as a convenient
channel exchanging ideas or as an unexpected conduit circulating fake news
through a large population. While existing studies of fake news focus on
theoretical modeling of propagation or identification methods based on machine
learning, it is important to understand the realistic mechanisms between
theoretical models and black-box methods. Here we track large databases of fake
news and real news in both, Weibo in China and Twitter in Japan from different
culture, which include their complete traces of re-postings. We find in both
online social networks that fake news spreads distinctively from real news even
at early stages of propagation, e.g. five hours after the first re-postings.
Our finding demonstrates collective structural signals that help to understand
the different propagation evolution of fake news and real news. Different from
earlier studies, identifying the topological properties of the information
propagation at early stages may offer novel features for early detection of
fake news in social media.
