  We study a unique network dataset including periodic surveys and electronic
logs of dyadic contacts via smartphones. The participants were a sample of
freshmen entering university in the Fall 2011. Their opinions on a variety of
political and social issues and lists of activities on campus were regularly
recorded at the beginning and end of each semester for the first three years of
study. We identify a behavioral network defined by call and text data, and a
cognitive network based on friendship nominations in ego-network surveys. Both
networks are limited to study participants. Since a wide range of attributes on
each node were collected in self-reports, we refer to these networks as
attribute-rich networks. We study whether student preferences for certain
attributes of friends can predict formation and dissolution of edges in both
networks. We introduce a method for computing student preferences for different
attributes which we use to predict link formation and dissolution. We then rank
these attributes according to their importance for making predictions. We find
that personal preferences, in particular political views, and preferences for
common activities help predict link formation and dissolution in both the
behavioral and cognitive networks.
