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Found 6 papers, 3 papers with code
A Simple Three-Step Approach for the Automatic Detection of Exaggerated Statements in Health Science News
There is a huge difference between a scientific journal reporting {`}wine consumption might be correlated to cancer{'}, and a media outlet publishing {`}wine causes cancer{'} citing the journal{'}s results.
Representation of professions in entertainment media: Insights into frequency and sentiment trends through computational text analysis
We analyze the frequency and sentiment trends of different occupations, study the effect of media attributes like genre, country of production, and title type on these trends, and investigate if the incidence of professions in media subtitles correlate with their real-world employment statistics.
Cross Domain Emotion Recognition using Few Shot Knowledge Transfer
Emotion recognition from text is a challenging task due to diverse emotion taxonomies, lack of reliable labeled data in different domains, and highly subjective annotation standards.
Leveraging Label Correlations in a Multi-label Setting: A Case Study in Emotion
First, we develop two modeling approaches to the problem in order to capture word associations of the emotion words themselves, by either including the emotions in the input, or by leveraging Masked Language Modeling (MLM).
Using Emotion Embeddings to Transfer Knowledge Between Emotions, Languages, and Annotation Formats
In this work, we study how we can build a single model that can transition between these different configurations by leveraging multilingual models and Demux, a transformer-based model whose input includes the emotions of interest, enabling us to dynamically change the emotions predicted by the model.
