FrameFinder: Explorative Multi-Perspective Framing Extraction from News Headlines

Abstract

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.

Accepted for publication at CHIIR'24

References in corpus (4)

• Gradio: Hassle-Free Sharing and Testing of ML Models in the Wild
• Moral Framing and Ideological Bias of News
• Studying Moral-based Differences in the Framing of Political Tweets
• SheffieldVeraAI at SemEval-2023 Task 3: Mono and multilingual approaches for news genre, topic and persuasion technique classification