  Predicting the popularity of content is important for both the host and users
of social media sites. The challenge of this problem comes from the inequality
of the popularity of con- tent. Existing methods for popularity prediction are
mainly based on the quality of content, the interface of social media site to
highlight contents, and the collective behavior of user- s. However, little
attention is paid to the structural charac- teristics of the networks spanned
by early adopters, i.e., the users who view or forward the content in the early
stage of content dissemination. In this paper, taking the Sina Weibo as a case,
we empirically study whether structural character- istics can provide clues for
the popularity of short messages. We find that the popularity of content is
well reflected by the structural diversity of the early adopters. Experimental
results demonstrate that the prediction accuracy is signif- icantly improved by
incorporating the factor of structural diversity into existing methods.
