  The rise of social media platforms has fundamentally altered the public
discourse by providing easy to use and ubiquitous forums for the exchange of
ideas and opinions. Elected officials often use such platforms for
communication with the broader public to disseminate information and engage
with their constituencies and other public officials. In this work, we
investigate whether Twitter conversations between legislators reveal their
real-world position and influence by analyzing multiple Twitter networks that
feature different types of link relations between the Members of Parliament
(MPs) in the United Kingdom and an identical data set for politicians within
Ireland. We develop and apply a matrix factorization technique that allows the
analyst to emphasize nodes with contextual local network structures by
specifying network statistics that guide the factorization solution. Leveraging
only link relation data, we find that important politicians in Twitter networks
are associated with real-world leadership positions, and that rankings from the
proposed method are correlated with the number of future media headlines.
