@guojing
@lemmy.mlhttps://davidrozado.substack.com/p/the-increasing-negativity-and-emotionality
Published article Introduction I have recently published a paper where we describe a chronological (2000–2019) analysis of sentiment and emotion in 23 million headlines from 47 news media outlets popular in the United States. We used Transformer language models fine-tuned for detection of sentiment (positive, negative) and emotions (anger, disgust, fear, joy, sadness, neutral) to automatically label the headlines.
https://www.globaltimes.cn/page/202202/1253228.shtml