{"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":"codex-gemma-dda1882f352a","candidate_categories":[],"consensus_categories":[],"category_scores_codex":[0.0005478249,0.00008598041,0.0001815539,0.0002979757,0.0001169471,0.0002458327,0.0002583505,0.0000318561,0.00004747288],"category_scores_gemma":[0.00003370881,0.0000739402,0.0001908343,0.0007695917,0.00001016487,0.0004840494,0.0000769373,0.00003036167,0.00001555224],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.00006468258,"about_ca_system_score_gemma":0.00003459134,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00002744166,"about_ca_topic_score_gemma":0.00001719474,"domain_scores_codex":[0.999052,0.00006320307,0.0002087301,0.0002552764,0.0002605217,0.0001602525],"domain_scores_gemma":[0.9993737,0.0001481911,0.0001255042,0.0001473172,0.0001316692,0.00007356229],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"simulation_or_modeling","study_design_gemma":"simulation_or_modeling","study_design_scores_codex":[0.0003575677,0.001768442,0.0693194,0.00005927923,0.0221819,0.00002305806,0.07316616,0.4015783,0.01575261,0.1415197,0.07936587,0.1949078],"study_design_scores_gemma":[0.0002710533,0.00001534844,0.0003930226,0.00000193062,0.0002502998,4.640889e-7,0.0004694197,0.9933466,0.003228911,0.0004266568,0.001481166,0.0001151439],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.007267811,0.00002583879,0.9915717,0.0002021452,0.0003807815,0.00007387857,4.499525e-7,0.00005425061,0.0004231889],"genre_scores_gemma":[0.6369211,0.000001037064,0.3624156,0.0001148694,0.0002652928,0.000009028316,0.00001003834,0.00000493982,0.0002580586],"genre_candidate":"methods","genre_consensus":null,"teacher_disagreement_score":0.6296533,"threshold_uncertainty_score":0.3015194,"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."}}