  How an information spreads throughout a social network is a valuable
knowledge sought by many groups such as marketing enterprises and political
parties. If they can somehow predict the impact of a given message or
manipulate it in order to amplify how long it will spread, it would give them a
huge advantage over their competitors. Intuitively, it is expected that two
factors contribute to make an information becoming viral: how influential the
person who spreads is inside its network and the content of the message. The
former should have a more important role, since people will not just blindly
share any content, or will they? In this work it is found that the degree of a
node alone is capable of accurately predicting how many followers of the seed
user will spread the information through a simple linear regression. The
analysis was performed with five different messages from Twitter network that
was shared with different degrees along the users. The results show evidences
that no matter the content, the number of affected neighbors is predictable.
The role of the content of the messages of a user is likely to influence the
network formation and the path the message will follow through the network.
