{"id":"W3110640267","doi":"10.5539/ijel.v11n1p99","title":"Linguistic-Based Detection of Fake News in Social Media","year":2020,"lang":"en","type":"article","venue":"International Journal of English Linguistics","topic":"Misinformation and Its Impacts","field":"Social Sciences","cited_by":60,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Computer science; Social media; Test (biology); Filter (signal processing); Natural language processing; Fake news; Set (abstract data type); Linguistic analysis; Field (mathematics); Linguistics; Artificial intelligence; Information retrieval; World Wide Web; Internet privacy; Mathematics","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":true,"about_ca":false,"invisible_to_affiliation_only":true},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.003128637,0.0002623604,0.0003011916,0.009391849,0.0006856665,0.001889881,0.0003357583,0.0005811842,0.001105839],"category_scores_gemma":[0.02374407,0.0001310278,0.0002628388,0.003364618,0.000739961,0.001831965,0.000961823,0.0004618921,0.0005771888],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0005842293,"about_ca_system_score_gemma":0.0003795075,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001469917,"about_ca_topic_score_gemma":0.001962455,"domain_scores_codex":[0.9967991,0.001499046,0.0003330219,0.0003550102,0.0008540783,0.0001595497],"domain_scores_gemma":[0.9675694,0.01952739,0.006789649,0.001735986,0.00398594,0.0003916416],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001274373,0.000579612,0.6269932,0.002298555,0.0001779811,0.001473036,0.02530183,0.001908435,0.04494952,0.005773121,0.00725353,0.2820168],"study_design_scores_gemma":[0.00002609866,0.0003586609,0.9022044,0.0004069562,0.0001371577,0.001243022,0.02009576,0.03608134,0.02212519,0.003304845,0.01390693,0.0001096681],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9848166,0.0003215951,0.006158315,0.0003415146,0.00003680422,0.0001299591,0.001962145,0.0001297557,0.006103276],"genre_scores_gemma":[0.9892094,0.0001611777,0.008008363,0.00004203417,0.00004989739,0.00009586682,0.001617208,0.00001482216,0.0008012468],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.009391849,"threshold_uncertainty_score":0.01654601,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.04093300493071868,"score_gpt":0.3304429687366355,"score_spread":0.2895099638059169,"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."}}