{"id":"W4214810516","doi":"10.1504/ijeg.2021.121241","title":"Sentiment analysis of political discussion on Twitter in Nigeria's 2019 presidential election","year":2021,"lang":"en","type":"article","venue":"International Journal of Electronic Governance","topic":"Hate Speech and Cyberbullying Detection","field":"Computer Science","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Presidential election; Social media; Politics; Presidential system; Sentiment analysis; Political science; General election; Representation (politics); Ideology; Political communication; Public relations; Lexicon; Media studies; Sociology; Computer science; Law; Artificial intelligence","routes":{"ca_aff":false,"ca_fund":false,"ca_venue":false,"about_ca":true,"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":[0.0004063678,0.0001574357,0.0002321472,0.001000966,0.0006162173,0.0008055243,0.0001024196,0.0002542223,0.001406788],"category_scores_gemma":[0.001371421,0.00007084516,0.0001745295,0.0009148015,0.0002190188,0.0006267083,0.0003927482,0.0002724734,0.0005961393],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002742823,"about_ca_system_score_gemma":0.0001897161,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.001809339,"about_ca_topic_score_gemma":0.004022692,"domain_scores_codex":[0.9996628,0.00009557413,0.00003269417,0.00004316376,0.00009435235,0.00007145465],"domain_scores_gemma":[0.9992772,0.0002946251,0.0001474803,0.00002625221,0.0001982798,0.00005628797],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.001943103,0.0004181722,0.7301082,0.001050953,0.0001278042,0.002415558,0.03302968,0.001329749,0.04697546,0.002672435,0.02100245,0.1589264],"study_design_scores_gemma":[0.0000120164,0.0002086186,0.9237071,0.0001177094,0.0000688242,0.0003664526,0.03351829,0.008071411,0.008357732,0.0005194511,0.02500537,0.00004697074],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9934388,0.0001428407,0.0003329337,0.0002334321,0.00006601849,0.00002625646,0.0009704496,0.00001784813,0.004771417],"genre_scores_gemma":[0.9953457,0.0001786576,0.0005156779,0.00005885922,0.00007501691,0.00005518618,0.001163585,0.00001022398,0.002597085],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.001809339,"threshold_uncertainty_score":0.004706204,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.004501113774446315,"score_gpt":0.2568855064945709,"score_spread":0.2523843927201245,"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."}}