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.
| Original language | English |
|---|---|
| Title of host publication | CHIIR 2024 - Proceedings of the 2024 Conference on Human Information Interaction and Retrieval |
| Publisher | Association for Computing Machinery (ACM) |
| Pages | 381-385 |
| Number of pages | 5 |
| ISBN (Electronic) | 9798400704345 |
| DOIs | |
| Publication status | Published - 10 Mar 2024 |
| Event | 2024 Conference on Human Information Interaction and Retrieval: CHIIR 2024 - Sheffield, United Kingdom Duration: 10 Mar 2024 → 14 Mar 2024 |
Publication series
| Name | CHIIR 2024 - Proceedings of the 2024 Conference on Human Information Interaction and Retrieval |
|---|
Conference
| Conference | 2024 Conference on Human Information Interaction and Retrieval |
|---|---|
| Country/Territory | United Kingdom |
| City | Sheffield |
| Period | 10/03/24 → 14/03/24 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 16 Peace, Justice and Strong Institutions
Keywords
- Computational Framing Extraction
- Exploratory Content Analysis
- Media Bias
- Online News
- Text Representations
ASJC Scopus subject areas
- Human-Computer Interaction
- Information Systems
- Information Systems and Management
- Experimental and Cognitive Psychology
Fields of Expertise
- Information, Communication & Computing
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