Human Interest Framing across Cultures: A Case Study on Climate Change
Abstract: Human Interest (HI) framing is a narrative strategy that injects news stories with a relatable, emotional angle and a human face, to engage the audience.
In this study we investigate the use of HI framing across different cultures in news articles about climate change.
Despite having a high impact in the public's behaviour and perception of an issue, HI framing has been under-explored in NLP to date.
We perform a systematic analysis of HI-stories across cultures to understand its role in climate change reporting.
Our findings reveal key differences in \textit{how} climate change is portrayed across countries, encompassing aspects such as narrative roles, article polarity, pronoun prevalence, and topics.
We also demonstrate that these linguistic aspects boost the performance of fine-tuned transformers on HI story classifications.
Paper Type: Long
Research Area: Computational Social Science and Cultural Analytics
Research Area Keywords: frame detection and analysis,cultural analysis
Contribution Types: Data resources, Data analysis
Languages Studied: English
Submission Number: 420
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