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Capturing Changes in Mood Over Time in Longitudinal Data Using Ensemble Methodologies
This paper presents the system description of team BLUE for Task A of the CLPsych 2022 Shared Task on identifying changes in mood and behaviour in longitudinal textual data.
Generalizable Sarcasm Detection Is Just Around The Corner, Of Course!
We tested the robustness of sarcasm detection models by examining their behavior when fine-tuned on four sarcasm datasets containing varying characteristics of sarcasm: label source (authors vs. third-party), domain (social media/online vs. offline conversations/dialogues), style (aggressive vs. humorous mocking).
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