{"id":"https://openalex.org/W4361793623","doi":"https://doi.org/10.1145/3582197.3582200","title":"Text Sentiment Analysis Based on CNN-BiGRU Enhanced Features","display_name":"Text Sentiment Analysis Based on CNN-BiGRU Enhanced Features","publication_year":2022,"publication_date":"2022-12-23","ids":{"openalex":"https://openalex.org/W4361793623","doi":"https://doi.org/10.1145/3582197.3582200"},"language":"en","primary_location":{"id":"doi:10.1145/3582197.3582200","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1145/3582197.3582200","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3582197.3582200?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 10th International Conference on Information Technology: IoT and Smart City","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3582197.3582200?download=true","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5001668150","display_name":"Jiahui Zhu","orcid":"https://orcid.org/0000-0002-4082-5248"},"institutions":[{"id":"https://openalex.org/I23632641","display_name":"Shanghai University of Electric Power","ror":"https://ror.org/02w4tny03","country_code":"CN","type":"education","lineage":["https://openalex.org/I23632641"]},{"id":"https://openalex.org/I4210120238","display_name":"PowerChina (China)","ror":"https://ror.org/01varr368","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210120238"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jiahui Zhu","raw_affiliation_strings":["Shanghai University of Electric Power, China"],"raw_orcid":"https://orcid.org/0000-0002-4082-5248","affiliations":[{"raw_affiliation_string":"Shanghai University of Electric Power, China","institution_ids":["https://openalex.org/I23632641","https://openalex.org/I4210120238"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5030826621","display_name":"Haiming Li","orcid":"https://orcid.org/0000-0002-8455-7409"},"institutions":[{"id":"https://openalex.org/I23632641","display_name":"Shanghai University of Electric Power","ror":"https://ror.org/02w4tny03","country_code":"CN","type":"education","lineage":["https://openalex.org/I23632641"]},{"id":"https://openalex.org/I4210120238","display_name":"PowerChina (China)","ror":"https://ror.org/01varr368","country_code":"CN","type":"company","lineage":["https://openalex.org/I4210120238"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Haiming Li","raw_affiliation_strings":["Shanghai University of Electric Power, China"],"raw_orcid":"https://orcid.org/0000-0002-8455-7409","affiliations":[{"raw_affiliation_string":"Shanghai University of Electric Power, China","institution_ids":["https://openalex.org/I23632641","https://openalex.org/I4210120238"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.1687,"has_fulltext":true,"cited_by_count":1,"citation_normalized_percentile":{"value":0.48516937,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":"13","issue":null,"first_page":"15","last_page":"21"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9980999827384949,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11550","display_name":"Text and Document Classification Technologies","score":0.9865000247955322,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9840999841690063,"subfield":{"id":"https://openalex.org/subfields/1702","display_name":"Artificial Intelligence"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.8431547284126282},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7769678831100464},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6557738184928894},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6462526321411133},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.616301417350769},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.5018253326416016},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.49247345328330994},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4834609925746918},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4297640323638916},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.05358964204788208}],"concepts":[{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.8431547284126282},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7769678831100464},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6557738184928894},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6462526321411133},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.616301417350769},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.5018253326416016},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.49247345328330994},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4834609925746918},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4297640323638916},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.05358964204788208},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3582197.3582200","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1145/3582197.3582200","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3582197.3582200?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 10th International Conference on Information Technology: IoT and Smart City","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3582197.3582200","is_oa":true,"landing_page_url":"http://dx.doi.org/10.1145/3582197.3582200","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3582197.3582200?download=true","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2022 10th International Conference on Information Technology: IoT and Smart City","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4361793623.pdf"},"referenced_works_count":16,"referenced_works":["https://openalex.org/W1984892353","https://openalex.org/W2751795976","https://openalex.org/W2757541972","https://openalex.org/W2801716390","https://openalex.org/W2910645120","https://openalex.org/W2971220558","https://openalex.org/W2998964503","https://openalex.org/W3005043037","https://openalex.org/W3019399664","https://openalex.org/W3080601402","https://openalex.org/W4226128467","https://openalex.org/W4236723364","https://openalex.org/W4237040408","https://openalex.org/W6601691205","https://openalex.org/W6605177870","https://openalex.org/W6611451672"],"related_works":["https://openalex.org/W4293226380","https://openalex.org/W4321487865","https://openalex.org/W4313906399","https://openalex.org/W4391266461","https://openalex.org/W2590798552","https://openalex.org/W2811106690","https://openalex.org/W4239306820","https://openalex.org/W2947043951","https://openalex.org/W4399188509","https://openalex.org/W4312417841"],"abstract_inverted_index":{"In":[0],"order":[1],"to":[2,12,52,65,79,90],"solve":[3],"the":[4,14,28,54,85,93,98,103,107],"problem":[5],"that":[6,111],"traditional":[7],"neural":[8,36,41],"network":[9,37],"models":[10],"tend":[11],"ignore":[13],"importance":[15],"between":[16],"aspect":[17,32,55,66,123],"words":[18,56,67],"and":[19,21,26,43,70,83,101,126],"context,":[20],"can":[22,119],"not":[23],"fully":[24],"obtain":[25,80,120],"utilize":[27],"corresponding":[29],"features":[30,57,74,96,100],"in":[31],"sentiment":[33],"analysis":[34],"task.A":[35],"model":[38,60,118],"of":[39,97,106],"convolutional":[40],"network(CNN)":[42],"bidirectional":[44],"gated":[45],"recurrent":[46],"unit(BiGRU)":[47],"based":[48],"on":[49],"attention":[50,86],"mechanism":[51,87],"enhance":[53],"is":[58,88],"proposed.The":[59],"enhances":[61],"feature":[62],"information":[63],"related":[64],"through":[68],"CNN":[69],"BiGRU.Then":[71],"The":[72],"enhanced":[73],"are":[75,129],"used":[76,89],"by":[77],"BiGRU":[78],"global":[81,99],"features,":[82],"finally":[84],"screen":[91],"out":[92],"most":[94],"relevant":[95,122],"get":[102],"emotion":[104],"category":[105],"text.Experimental":[108],"results":[109],"show":[110],"compared":[112],"with":[113],"other":[114,132],"baseline":[115],"models,":[116],"this":[117],"more":[121],"features.The":[124],"accuracy":[125],"F1":[127],"values":[128],"better":[130],"than":[131],"models.":[133]},"counts_by_year":[{"year":2024,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}