{"id":"W2588795443","doi":"","title":"Hashtag Politics: A Twitter sentiment analysis of the 2015 Canadian Election using a randomized block design model","year":2016,"lang":"en","type":"article","venue":"MacEwan University Student Research Proceedings","topic":"Social Media and Politics","field":"Social Sciences","cited_by":0,"is_retracted":false,"has_abstract":false,"ca_institutions":"","funders":"","keywords":"Politics; Block (permutation group theory); Sentiment analysis; Computer science; Social media; Political science; World Wide Web; Artificial intelligence; Mathematics; Law; Combinatorics","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":[0.01303076,0.0008687203,0.00130954,0.0007241684,0.002606544,0.001304032,0.002245121,0.001175323,0.01377209],"category_scores_gemma":[0.02914267,0.0006123179,0.001540902,0.001414719,0.001333587,0.0008132957,0.0007763762,0.001857525,0.001049254],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.008541648,"about_ca_system_score_gemma":0.01513486,"about_ca_topic_candidate":true,"about_ca_topic_consensus":true,"about_ca_topic_score_codex":0.6874704,"about_ca_topic_score_gemma":0.7270498,"domain_scores_codex":[0.9940249,0.003998319,0.0001150773,0.0006319144,0.0005645506,0.0006653209],"domain_scores_gemma":[0.9795325,0.01537379,0.0009792619,0.001486515,0.002037192,0.0005907358],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.06124784,0.009678598,0.3188919,0.001476004,0.005884494,0.0005680716,0.005528406,0.2441076,0.01147294,0.06744274,0.07386143,0.19984],"study_design_scores_gemma":[0.006912797,0.0042391,0.3231601,0.00009779343,0.003062989,0.00006837559,0.002465123,0.6114647,0.003252411,0.01296681,0.0319386,0.0003710889],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9507926,0.0002787736,0.03124347,0.0009572727,0.0002477577,0.002642976,0.008777155,0.0004032154,0.004656775],"genre_scores_gemma":[0.9639603,0.0001092963,0.01745886,0.0002359891,0.00007423447,0.002684475,0.006270099,0.000108972,0.009097775],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.3125296,"threshold_uncertainty_score":0.6287402,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.1448626393351864,"score_gpt":0.4121089606510002,"score_spread":0.2672463213158137,"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."}}