{"id":"W4317515583","doi":"10.1109/ccis57298.2022.10016405","title":"A Joint Learning Sentiment Analysis Method Incorporating Emoji-Augmentation","year":2022,"lang":"en","type":"article","venue":"2022 IEEE 8th International Conference on Cloud Computing and Intelligent Systems (CCIS)","topic":"Sentiment Analysis and Opinion Mining","field":"Computer Science","cited_by":2,"is_retracted":false,"has_abstract":true,"ca_institutions":"Artificial Intelligence in Medicine (Canada)","funders":"Chizhou University; National Natural Science Foundation of China","keywords":"Emoji; Computer science; Sentiment analysis; Artificial intelligence; Semantics (computer science); Social media; Natural language processing; Sentence; Feeling; Joint (building); Microblogging; World Wide Web; Psychology","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":["metaepi_narrow"],"consensus_categories":[],"category_scores_codex":[0.002545787,0.0003348996,0.0005535082,0.000967831,0.0009386866,0.0008607061,0.0009073897,0.00005627637,0.0003792728],"category_scores_gemma":[0.00004809719,0.0003452078,0.0003048634,0.001203126,0.00003208553,0.0002066955,0.0007118579,0.0005825957,0.00004411626],"about_ca_system_candidate":false,"about_ca_system_consensus":false,"about_ca_system_score_codex":0.0003349936,"about_ca_system_score_gemma":0.00007279279,"about_ca_topic_candidate":false,"about_ca_topic_consensus":false,"about_ca_topic_score_codex":0.0002491056,"about_ca_topic_score_gemma":0.000006093695,"domain_scores_codex":[0.995306,0.0008699713,0.001076628,0.001010633,0.001374896,0.0003618619],"domain_scores_gemma":[0.9979513,0.0002277967,0.0009809434,0.0004101784,0.0002768111,0.0001529648],"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":[0.00004709679,0.0002845836,0.01200739,0.00004720896,0.002342975,0.00003935404,0.004184099,0.7414473,0.002566841,0.2083762,0.001247322,0.02740959],"study_design_scores_gemma":[0.0002872175,0.0002232239,0.0002869941,0.00006410379,0.0001095533,0.00002683852,0.00386028,0.991855,0.0008709744,0.0003545585,0.001703968,0.0003573423],"study_design_candidate":"simulation_or_modeling","study_design_consensus":"simulation_or_modeling","genre_codex":"methods","genre_gemma":"empirical","genre_scores_codex":[0.086197,0.000185628,0.9051197,0.000671886,0.004209411,0.0003060428,0.0000117819,0.0001903695,0.00310825],"genre_scores_gemma":[0.9917742,0.00004091363,0.005767416,0.0002425679,0.0003384368,0.00004858179,0.00009348623,0.00001903746,0.001675342],"genre_candidate":"empirical","genre_consensus":null,"teacher_disagreement_score":0.9055772,"threshold_uncertainty_score":0.9999,"prediction_status":"machine_predicted_unvalidated"},"machine_scores":{"provisional":true,"baseline":true,"maturity_gate_passed":false,"score_opus":0.06592982217907196,"score_gpt":0.3367143573870326,"score_spread":0.2707845352079607,"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."}}