{"id":"W2120120501","doi":"10.5539/ass.v10n18p144","title":"Who Is Tweeting on #PRU13?","year":2014,"lang":"en","type":"article","venue":"Asian Social Science","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":6,"is_retracted":false,"has_abstract":true,"ca_institutions":"","funders":"","keywords":"Social media; Timeline; Microblogging; Opposition (politics); General election; Politics; Political science; Thematic analysis; Public relations; Media studies; Political communication; Advertising; Sociology; Qualitative research; Social science; Business; Law; History","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":[0.0007427746,0.0001964874,0.0002767794,0.001105603,0.0009898589,0.002001882,0.0001996446,0.0008009322,0.007914657],"category_scores_gemma":[0.005570696,0.0001621452,0.0002494063,0.001643688,0.0003074952,0.002076907,0.0004663141,0.0005824657,0.005819709],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0004170205,"about_ca_system_score_gemma":0.0002447223,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.004222183,"about_ca_topic_score_gemma":0.008355063,"domain_scores_codex":[0.9993136,0.0002119385,0.00006275529,0.0001126,0.0001617294,0.00013737],"domain_scores_gemma":[0.9972146,0.001068776,0.0007893188,0.0001128902,0.0005321945,0.0002821441],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0007667895,0.00009646418,0.61224,0.0009149536,0.0002090753,0.001240802,0.01937549,0.0003080657,0.007433567,0.005663376,0.127375,0.2243764],"study_design_scores_gemma":[0.00001806797,0.000212039,0.6740255,0.0004656722,0.000195499,0.00236718,0.04150314,0.003575805,0.006183624,0.002135594,0.2691984,0.0001194825],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.8872421,0.002702804,0.003832037,0.01618411,0.001808492,0.0001332791,0.01215828,0.0003158051,0.07562301],"genre_scores_gemma":[0.9703523,0.001691431,0.001315406,0.00163939,0.0008357467,0.0000783955,0.003242574,0.0001048299,0.0207399],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.007914657,"threshold_uncertainty_score":0.02647716,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.01665240758136402,"score_gpt":0.285070835397521,"score_spread":0.2684184278161569,"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."}}