{"id":"W4285109023","doi":"10.1017/dsj.2022.12","title":"Communication patterns in engineering enterprise social networks: an exploratory analysis using short text topic modelling","year":2022,"lang":"en","type":"article","venue":"Design Science","topic":"Design Education and Practice","field":"Engineering","cited_by":15,"is_retracted":false,"has_abstract":true,"ca_institutions":"University of Toronto","funders":"","keywords":"Computer science; Social network analysis; Set (abstract data type); Knowledge management; New product development; Social network (sociolinguistics); Exploratory research; Data science; Product (mathematics); Process (computing); Product design; Social media; World Wide Web; Management; Sociology","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":[0.004338996,0.0003810966,0.0003638434,0.005365441,0.0006284182,0.001426824,0.0006695163,0.0005912407,0.001218416],"category_scores_gemma":[0.02088769,0.0002396204,0.0007915451,0.00540959,0.0006549715,0.001825516,0.001085018,0.0006494936,0.0003569019],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0008064017,"about_ca_system_score_gemma":0.000532953,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.00410495,"about_ca_topic_score_gemma":0.003783279,"domain_scores_codex":[0.9967879,0.002035194,0.000233781,0.0003511732,0.0004610938,0.0001309504],"domain_scores_gemma":[0.9531446,0.04066181,0.00273353,0.001395481,0.001758681,0.0003058976],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0008166212,0.0008339761,0.7059619,0.001360767,0.0004330519,0.001003415,0.08889503,0.02611831,0.01117904,0.009017123,0.003441909,0.1509389],"study_design_scores_gemma":[0.00007179299,0.0005998572,0.5742788,0.0003031287,0.0001741404,0.0008328752,0.05392171,0.3406632,0.005057877,0.01306345,0.01090245,0.0001307236],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.9747468,0.0001098809,0.02186926,0.0001754308,0.000008738834,0.0002684983,0.001697307,0.00007533587,0.00104886],"genre_scores_gemma":[0.9785479,0.00007463762,0.01840161,0.00001967876,0.00001611729,0.0005605323,0.001949172,0.00002303444,0.0004073423],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.005365441,"threshold_uncertainty_score":0.02294707,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.07802889857386103,"score_gpt":0.3001244374811094,"score_spread":0.2220955389072484,"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."}}