{"id":"W1654173042","doi":"","title":"Unsupervised Modeling of Twitter Conversations","year":2010,"lang":"en","type":"article","venue":"NPARC","topic":"Topic Modeling","field":"Computer Science","cited_by":434,"is_retracted":false,"has_abstract":true,"ca_institutions":"National Research Council Canada","funders":"Microsoft Research","keywords":"Computer science; Conversation; Task (project management); Cluster analysis; Visualization; Domain (mathematical analysis); Artificial intelligence; Social media; Natural language processing; Microblogging; Topic model; Data science; World Wide Web; Linguistics","routes":{"ca_aff":true,"ca_fund":false,"ca_venue":true,"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":[0.001008454,0.0005647665,0.0005435738,0.001160927,0.0005663057,0.001183551,0.001118301,0.0007092286,0.001428792],"category_scores_gemma":[0.006810176,0.0004108484,0.0007966434,0.0008705125,0.0006282655,0.001916764,0.001034436,0.001079712,0.0006879616],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0007663103,"about_ca_system_score_gemma":0.0007617376,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.005841764,"about_ca_topic_score_gemma":0.007299322,"domain_scores_codex":[0.9989691,0.0004945821,0.00004307236,0.0002786739,0.0001232621,0.00009131733],"domain_scores_gemma":[0.9976798,0.001403945,0.0002683688,0.0002877445,0.00027171,0.00008854204],"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":[0.0005433768,0.0002388259,0.02698207,0.0003584452,0.0002629847,0.0004497948,0.003433864,0.6984304,0.01961686,0.09021916,0.009850348,0.1496139],"study_design_scores_gemma":[0.000004942787,0.000009051157,0.00121353,0.000005403518,0.000006131157,0.00002595493,0.00006912276,0.9860108,0.0006517785,0.01067461,0.001320543,0.00000821147],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.11056,0.0002992035,0.8813415,0.000597939,0.00005559218,0.0001543512,0.001693289,0.001068754,0.004229306],"genre_scores_gemma":[0.8848689,0.0003092695,0.1065673,0.00009910824,0.0001573223,0.0004229722,0.002932727,0.0002598317,0.004382703],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.005841764,"threshold_uncertainty_score":0.01161551,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.03234468296183593,"score_gpt":0.247503627607715,"score_spread":0.215158944645879,"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."}}