{"id":"W2045736743","doi":"10.1145/2775441.2775472","title":"Using social media sentiment analysis for interaction design choices","year":2015,"lang":"en","type":"article","venue":"","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":7,"is_retracted":false,"has_abstract":true,"ca_institutions":"McMaster University","funders":"","keywords":"Sentiment analysis; Computer science; Social media; Interaction design; Human–computer interaction; Data science; World Wide Web; Artificial intelligence","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":false,"about_ca":false,"invisible_to_affiliation_only":false},"retraction":null,"screen":null,"direct_labels":[],"prediction":{"model_version":"metacan-v3-hybrid-931329e0061c","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0165468,0.001651704,0.0007459163,0.003087647,0.00214275,0.007039759,0.001050232,0.001012832,0.005059197],"category_scores_gemma":[0.04755345,0.0008239535,0.001132039,0.001186108,0.0014411,0.006820439,0.002010908,0.001470826,0.001793152],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.001986812,"about_ca_system_score_gemma":0.001360968,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0007884158,"about_ca_topic_score_gemma":0.002051613,"domain_scores_codex":[0.9822332,0.01224223,0.00101767,0.001008453,0.003045132,0.0004535084],"domain_scores_gemma":[0.9708302,0.01741829,0.001983791,0.001624245,0.007339022,0.0008044558],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"design_other","study_design_gemma":"not_applicable","study_design_scores_codex":[0.001965041,0.0007823504,0.03711531,0.0028312,0.0006739193,0.001202797,0.04923608,0.01096035,0.1178841,0.1263708,0.02943452,0.6215436],"study_design_scores_gemma":[0.0005732734,0.001920621,0.03083522,0.001835708,0.001638457,0.001031434,0.042197,0.2891598,0.1097054,0.233792,0.2867544,0.0005567142],"study_design_candidate":"not_applicable","study_design_consensus":null,"genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.1503978,0.0005533664,0.7823056,0.005922438,0.0003046577,0.001759959,0.0005978758,0.002233927,0.05592442],"genre_scores_gemma":[0.5755376,0.0003107827,0.416395,0.0005479089,0.00008901211,0.001394288,0.0004856987,0.0007092061,0.004530486],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.0165468,"threshold_uncertainty_score":0.08750892,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.2838293214497852,"score_gpt":0.3831155893769815,"score_spread":0.09928626792719636,"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."}}