{"id":"W3217598503","doi":"10.32920/ryerson.14645355.v1","title":"Microblog summarization based on sentiment and aspect analysis","year":2021,"lang":"en","type":"preprint","venue":"","topic":"Advanced Text Analysis Techniques","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Wilfrid Laurier University; Toronto Metropolitan University; University of Waterloo","funders":"","keywords":"Automatic summarization; Microblogging; Sentiment analysis; Social media; Computer science; Information retrieval; Baseline (sea); Cluster analysis; Multi-document summarization; Annotation; Natural language processing; Data science; Artificial intelligence; World Wide Web","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":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0006930597,0.001136166,0.0007982749,0.004451926,0.0006023171,0.001315051,0.0004445013,0.0003787442,0.001614424],"category_scores_gemma":[0.003101898,0.000256519,0.0006801919,0.002733967,0.0001861312,0.001349597,0.000694063,0.0005549684,0.00148847],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003397359,"about_ca_system_score_gemma":0.0004570394,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001673668,"about_ca_topic_score_gemma":0.003068751,"domain_scores_codex":[0.99946,0.0001048222,0.00007159553,0.0001094962,0.0001914131,0.00006259992],"domain_scores_gemma":[0.9978855,0.000507356,0.0003027193,0.0001594099,0.001058135,0.00008685203],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.000607295,0.0002017588,0.007142151,0.0007999425,0.0001973835,0.0004161626,0.001306076,0.007150688,0.1412272,0.002301633,0.01794083,0.820709],"study_design_scores_gemma":[0.0001593561,0.001259743,0.05051811,0.000197985,0.000856948,0.001083964,0.003661247,0.6009088,0.2429446,0.01676985,0.08143871,0.0002006558],"study_design_candidate":"simulation_or_modeling","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.2387021,0.002208334,0.731472,0.0008962441,0.0005006314,0.001331536,0.007077489,0.009661342,0.008150413],"genre_scores_gemma":[0.4250402,0.001433006,0.5469866,0.0001583611,0.0009456891,0.0007038745,0.01561259,0.00077277,0.008346947],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.004451926,"threshold_uncertainty_score":0.005400777,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.009684912507483769,"score_gpt":0.263804563741241,"score_spread":0.2541196512337572,"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."}}