  Understanding the dynamics of social interactions is crucial to comprehend
human behavior. The emergence of online social media has enabled access to data
regarding people relationships at a large scale. Twitter, specifically, is an
information oriented network, with users sharing and consuming information. In
this work, we study whether users tend to be in contact with people interested
in similar topics, i.e., if they are topically aligned. To do so, we propose an
approach based on the use of hashtags to extract information topics from
Twitter messages and model users' interests. Our results show that, on average,
users are connected with other users similar to them. Furthermore, we show that
topical alignment provides interesting information that can eventually allow
inferring users' connectivity. Our work, besides providing a way to assess the
topical similarity of users, quantifies topical alignment among individuals,
contributing to a better understanding of how complex social systems are
structured.
