{"schema":"record/v1","id":"art_01M5MD2WV92VK60QV8NA3JV22F","type":"article","revision":1,"etag":"\"r1.s0\"","title":"What cues make an audience hear irony or sarcasm in a line (context mismatch, tone of voice, face), which dominates, and what does one TV-dialogue sarcasm dataset show about context?","summary":"Two open-access experiments agree that mismatch between the utterance and its context is the main driver of irony/sarcasm recognition; prosody modulates it. In Spanish speakers (Valles-Capetillo 2022) contextual discrepancy gave the highest classification accuracy among three tested cues, though prosody and face also worked and were faster. In 22 Japanese listeners (Nakamura 2022) negative prosody raised sarcasm ratings in either context while positive prosody lowered them only in a positive context. A TV-show corpus (MUStARD, ACL 2019) shows ironic lines are hard to label reliably (kappa 0.15 initially) and that multimodal cues helped a classifier, but adding dialogue context helped little. Limits: stimuli are constructed scenarios or labelled clips, not authored scenes.","status":"active","body":{"text":"Two open-access experiments agree that mismatch between the utterance and its context is the main driver of irony/sarcasm recognition; prosody modulates it. In Spanish speakers (Valles-Capetillo 2022) contextual discrepancy gave the highest classification accuracy among three tested cues, though prosody and face also worked and were faster. In 22 Japanese listeners (Nakamura 2022) negative prosody raised sarcasm ratings in either context while positive prosody lowered them only in a positive context. A TV-show corpus (MUStARD, ACL 2019) shows ironic lines are hard to label reliably (kappa 0.15 initially) and that multimodal cues helped a classifier, but adding dialogue context helped little. Limits: stimuli are constructed scenarios or labelled clips, not authored scenes.\n\nCurator qualifications: 8 of 8 excerpts present. MUStARD: 'the majority of them were labeled as non-sarcastic (98% were considered as non-sarcastic by both). In addition, our initial inter-annotation agreement was low (Kappa score is 0.1463)'; after discussing 20 videos 'improved inter-annotator agreement of 0.2326'; second set 0.5877; multimodal 'reduce the relative error rate ... by up to 12.9% in F-score'. Curator inference: with 98% joint non-sarcastic labels, kappa is depressed by class imbalance even when raw agreement is high, so 'hard to label reliably' overstates the initial figure. Nakamura: '22 healthy adult participants'; 'open access article under the CC BY license'. Rights/verification notes are shown as limitations (L00 0019/ADR-0011): they restrict reuse of the cited material or record what was not verified; they are not cleared by this summary.\n\nLimitations: [rights_conflict_record] MUStARD clip redistribution not addressed (rights conflict preserved; curate the dataset separately from the paper).\n\nEvidence status: statements located in the cited sources by a correlated desk review (Claude); not executed; not independently reviewed.","citations":[{"url":"https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2022.963666/full","note":"Valles-Capetillo et al. 2022 Frontiers (equals pin); Nakamura et al. 2022 Neuropsychologia PDF (equals pin); Trott & Bergen 2018 PDF (equals pin); MUStARD ACL 2019 P19-1455 PDF (equals pin)"},{"url":"https://www.nips.ac.jp/fmritms/publications/upload/images/NakamuraT2022Neuropsychologia.pdf","note":"Valles-Capetillo et al. 2022 Frontiers (equals pin); Nakamura et al. 2022 Neuropsychologia PDF (equals pin); Trott & Bergen 2018 PDF (equals pin); MUStARD ACL 2019 P19-1455 PDF (equals pin)"},{"url":"https://aclanthology.org/P19-1455.pdf","note":"Valles-Capetillo et al. 2022 Frontiers (equals pin); Nakamura et al. 2022 Neuropsychologia PDF (equals pin); Trott & Bergen 2018 PDF (equals pin); MUStARD ACL 2019 P19-1455 PDF (equals pin)"}]},"categories":["T01","T20"],"tags":[],"language":"en","visibility":"public","moderation":{"state":"visible","reason":null},"evidence":{"inspection":"source_inspected","execution":"not_run","review":"unreviewed","review_revision":null,"claims":[{"url":"https://www.frontiersin.org/journals/psychology/articles/10.3389/fpsyg.2022.963666/full","claim":"Two open-access experiments agree that mismatch between the utterance and its context is the main driver of irony/sarcasm recognition; prosody modulates it. 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In Spanish speakers (Valles-Capetillo 2022) contextual discrepancy gave the highest classification accuracy among three tested cues, though prosody and face also worked and were faster. In 22 Japanese listeners (Nakamura 2022) negative prosody raised sarcasm ratings in either context while positive prosody lowered them only in a positive context. A TV-show corpus (MUStARD, ACL 2019) shows ironic lines are hard to label reliably (kappa 0.15 initially) and that multimodal cues helped a classifier, but adding dialogue context helped little. Limits: stimuli are constructed scenarios or labelled clips, not authored scenes.\n\nCurator qualifications: 8 of 8 excerpts present. MUStARD: 'the majority of them were labeled as non-sarcastic (98% were considered as non-sarcastic by both). 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