  Revealing the framing of news articles is an important yet neglected task in
information seeking and retrieval. In the present work, we present FrameFinder,
an open tool for extracting and analyzing frames in textual data. FrameFinder
visually represents the frames of text from three perspectives, i.e., (i) frame
labels, (ii) frame dimensions, and (iii) frame structure. By analyzing the
well-established gun violence frame corpus, we demonstrate the merits of our
proposed solution to support social science research and call for subsequent
integration into information interactions.
