{"id":"W3007289217","doi":"10.31542/muse.v4i1.877","title":"Hashtag Politics: A Twitter Sentiment Analysis of the 2015 Canadian Federal Election","year":2020,"lang":"en","type":"article","venue":"MacEwan University Student eJournal","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":4,"is_retracted":false,"has_abstract":true,"ca_institutions":"MacEwan University","funders":"","keywords":"Sentiment analysis; Federal election; Social media; Democracy; Politics; Political science; Application programming interface; Advertising; Computer science; Law; Business; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"about_ca":true,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0001529811,0.0001075529,0.000214102,0.0003962479,0.0004602929,0.0001562748,0.00087828,0.00003453895,0.0002031689],"category_scores_gemma":[0.000005707183,0.00009219279,0.0003414121,0.001545873,0.00003312838,0.0001806416,0.0002560187,0.0001587304,0.00001268068],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0002480726,"about_ca_system_score_gemma":0.0001681554,"about_ca_topic_candidate":true,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.007296705,"about_ca_topic_score_gemma":0.008175125,"domain_scores_codex":[0.9987069,0.0001171187,0.0001843086,0.0002392967,0.0004860749,0.0002662679],"domain_scores_gemma":[0.9991857,0.00001472108,0.000168701,0.0002276746,0.0001142214,0.0002890287],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0000124961,0.0001055588,0.9552966,0.000005422019,0.004017511,0.00006192871,0.01260192,0.004087433,0.0005135331,0.003347271,0.0193026,0.0006476712],"study_design_scores_gemma":[0.001205761,0.0001415635,0.8079739,0.00002419584,0.001687126,0.000009116553,0.007890274,0.1296005,0.001288798,0.00003620543,0.04971773,0.0004247735],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9068701,0.0000642165,0.05259207,0.03538609,0.0004295435,0.0001910959,0.00001377648,0.00004309799,0.004409989],"genre_scores_gemma":[0.9970072,0.000006603935,0.0004969247,0.001106717,0.00005962437,8.551295e-8,0.000002518936,0.000003099325,0.001317263],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.1473227,"threshold_uncertainty_score":0.9993138,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.0184583874679092,"score_gpt":0.248383415251715,"score_spread":0.2299250277838058,"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."}}