{"id":"W4308721738","doi":"10.3390/bdcc6040129","title":"Detecting and Understanding Sentiment Trends and Emotion Patterns of Twitter Users—A Study on the Demise of a Bollywood Celebrity","year":2022,"lang":"en","type":"article","venue":"Big Data and Cognitive Computing","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":8,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Calgary","funders":"","keywords":"Timeline; Sentiment analysis; Demise; Social media; Expression (computer science); Task (project management); Psychology; Emotion detection; Computer science; Natural language processing; History; Artificial intelligence; World Wide Web; Emotion recognition; Political science; Engineering","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0009683474,0.00010603,0.0001850351,0.0001561954,0.0004295513,0.00009795944,0.0002518405,0.00001279439,0.000005518015],"category_scores_gemma":[0.00004094477,0.00008724409,0.00002353146,0.0002863068,0.0000362551,0.0001135972,0.001708137,0.0001223789,7.317919e-8],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00001325256,"about_ca_system_score_gemma":0.000009400502,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00003817074,"about_ca_topic_score_gemma":0.000005236643,"domain_scores_codex":[0.9987031,0.0002370815,0.0002510165,0.0004097912,0.000265662,0.0001333278],"domain_scores_gemma":[0.999026,0.0004223135,0.0002397771,0.0002434622,0.00003494491,0.00003347617],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.00003872743,0.0003323896,0.5274516,0.00004452961,0.0003598603,0.00001120827,0.023734,0.00001894595,0.0006089963,0.0004166804,0.00003126082,0.4469518],"study_design_scores_gemma":[0.002414162,0.0008711146,0.5151016,0.0003250754,0.000293361,0.0000258627,0.1106034,0.3686727,0.001123041,0.0001859256,0.00002776638,0.0003559247],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8710431,0.00009219954,0.1284444,0.00015707,0.0000678756,0.0001067586,0.00002368853,0.000009286735,0.00005559454],"genre_scores_gemma":[0.9996982,0.000007040539,0.0001553515,0.00008441429,0.00002816015,0.000001778388,0.00001505517,0.000004523617,0.000005469153],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.4465958,"threshold_uncertainty_score":0.3557711,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1842424834947384,"score_gpt":0.3194875530399939,"score_spread":0.1352450695452555,"validation_status":"score_only:v0-immature-baseline","note":"Baseline scores from an immature model (maturity gate not passed). Scores rank; they never assert a category."}}