{"id":"W4389523864","doi":"10.18653/v1/2023.lchange-1.5","title":"A longitudinal study about gradual changes in the Iranian Online Public Sphere pre and post of ‘Mahsa Moment’: Focusing on Twitter","year":2023,"lang":"en","type":"article","venue":"","topic":"Complex Network Analysis Techniques","field":"Physics and Astronomy","cited_by":0,"is_retracted":false,"has_abstract":true,"ca_institutions":"Vector Institute","funders":"","keywords":"Event (particle physics); Cyberspace; Meaning (existential); Word (group theory); Computer science; Moment (physics); Cluster analysis; Artificial intelligence; History; World Wide Web; Linguistics; The Internet; Epistemology; Philosophy","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":[0.001090103,0.0001796955,0.0002243545,0.0007224859,0.00141504,0.001426899,0.0003225906,0.0007277334,0.003884045],"category_scores_gemma":[0.004362111,0.0001907058,0.0002192984,0.0009448274,0.0005555623,0.001814303,0.0009703272,0.001300033,0.001240035],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0006259612,"about_ca_system_score_gemma":0.0004772211,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0117234,"about_ca_topic_score_gemma":0.02277611,"domain_scores_codex":[0.9996135,0.0001133981,0.00002309498,0.00006266346,0.00007871079,0.00010859],"domain_scores_gemma":[0.9971029,0.0005839394,0.0009978529,0.0001776601,0.0006330972,0.000504509],"domain_codex":null,"domain_gemma":null,"domain_candidate":null,"domain_consensus":null,"study_design_codex":"observational","study_design_gemma":"observational","study_design_scores_codex":[0.0002561771,0.0008402992,0.9156832,0.00007611475,0.00007206675,0.0006286268,0.05791485,0.00009846412,0.001010315,0.000933005,0.006606406,0.0158804],"study_design_scores_gemma":[0.000005897527,0.0002133168,0.9412963,0.00002515494,0.00002450399,0.0001019394,0.05256223,0.0002814372,0.0002443768,0.0001519525,0.005068557,0.00002422828],"study_design_candidate":"observational","study_design_consensus":"observational","genre_codex":"empirical","genre_gemma":"empirical","genre_scores_codex":[0.997938,0.00005308379,0.0000586073,0.0003308716,0.0000198473,0.00001337605,0.0003375352,0.000002917605,0.001245728],"genre_scores_gemma":[0.9977404,0.000082832,0.00007878621,0.0001609255,0.00002848586,0.00003286729,0.0005526454,0.00000455147,0.001318516],"genre_candidate":"empirical","genre_consensus":"empirical","teacher_disagreement_score":0.0117234,"threshold_uncertainty_score":0.0233103,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06084547257480406,"score_gpt":0.326747989761991,"score_spread":0.2659025171871869,"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."}}