{"id":"https://openalex.org/W4387064081","doi":"https://doi.org/10.1109/icsecs58457.2023.10256397","title":"Analysis of Sentiment Towards Artificial Intelligent Industry Using Hybrid Natural Language Processing Technique","display_name":"Analysis of Sentiment Towards Artificial Intelligent Industry Using Hybrid Natural Language Processing Technique","publication_year":2023,"publication_date":"2023-08-25","ids":{"openalex":"https://openalex.org/W4387064081","doi":"https://doi.org/10.1109/icsecs58457.2023.10256397"},"language":"en","primary_location":{"id":"doi:10.1109/icsecs58457.2023.10256397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsecs58457.2023.10256397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 8th International Conference On Software Engineering and Computer Systems (ICSECS)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5112110031","display_name":"Chang Hyun Hong","orcid":"https://orcid.org/0009-0009-9569-0457"},"institutions":[{"id":"https://openalex.org/I4210134189","display_name":"Xiamen University Malaysia","ror":"https://ror.org/0331wa828","country_code":"MY","type":"education","lineage":["https://openalex.org/I191208505","https://openalex.org/I4210134189"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Chang Hong","raw_affiliation_strings":["School of Computing and Data Science, Xiamen University Malaysia,Sepang,Malaysia","School of Computing and Data Science, Xiamen University Malaysia, Sepang, Malaysia"],"raw_orcid":"https://orcid.org/0009-0009-9569-0457","affiliations":[{"raw_affiliation_string":"School of Computing and Data Science, Xiamen University Malaysia,Sepang,Malaysia","institution_ids":["https://openalex.org/I4210134189"]},{"raw_affiliation_string":"School of Computing and Data Science, Xiamen University Malaysia, Sepang, Malaysia","institution_ids":["https://openalex.org/I4210134189"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5112110031"],"corresponding_institution_ids":["https://openalex.org/I4210134189"],"apc_list":null,"apc_paid":null,"fwci":0.1704,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.56881436,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"363","last_page":"370"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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":0.9998999834060669,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.978600025177002,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12128","display_name":"AI in Service Interactions","score":0.9779000282287598,"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/transformative-learning","display_name":"Transformative learning","score":0.7355416417121887},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7265205383300781},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6162479519844055},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6008349061012268},{"id":"https://openalex.org/keywords/work","display_name":"Work (physics)","score":0.4551513195037842},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.39563414454460144},{"id":"https://openalex.org/keywords/risk-analysis","display_name":"Risk analysis (engineering)","score":0.3469087481498718},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.2089012861251831},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.15840813517570496},{"id":"https://openalex.org/keywords/sociology","display_name":"Sociology","score":0.11148911714553833}],"concepts":[{"id":"https://openalex.org/C70587473","wikidata":"https://www.wikidata.org/wiki/Q7834111","display_name":"Transformative learning","level":2,"score":0.7355416417121887},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7265205383300781},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6162479519844055},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6008349061012268},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.4551513195037842},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.39563414454460144},{"id":"https://openalex.org/C112930515","wikidata":"https://www.wikidata.org/wiki/Q4389547","display_name":"Risk analysis (engineering)","level":1,"score":0.3469087481498718},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2089012861251831},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.15840813517570496},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.11148911714553833},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C19417346","wikidata":"https://www.wikidata.org/wiki/Q7922","display_name":"Pedagogy","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icsecs58457.2023.10256397","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icsecs58457.2023.10256397","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 IEEE 8th International Conference On Software Engineering and Computer Systems (ICSECS)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Industry, innovation and infrastructure","id":"https://metadata.un.org/sdg/9","score":0.5199999809265137}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":15,"referenced_works":["https://openalex.org/W1662133657","https://openalex.org/W2099813784","https://openalex.org/W2155328222","https://openalex.org/W2168894761","https://openalex.org/W2220660951","https://openalex.org/W2340417948","https://openalex.org/W2963034284","https://openalex.org/W2982281530","https://openalex.org/W3011570378","https://openalex.org/W3035639004","https://openalex.org/W3102944297","https://openalex.org/W3173797296","https://openalex.org/W3200955930","https://openalex.org/W4385245566","https://openalex.org/W6604617241"],"related_works":["https://openalex.org/W2169196470","https://openalex.org/W3113185420","https://openalex.org/W4237580245","https://openalex.org/W4385368139","https://openalex.org/W2906134827","https://openalex.org/W4322745238","https://openalex.org/W4241245680","https://openalex.org/W3124327509","https://openalex.org/W3200688510","https://openalex.org/W4384833310"],"abstract_inverted_index":{"Artificial":[0],"Intelligence":[1],"(AI)":[2],"has":[3],"revolutionized":[4],"various":[5,159],"aspects":[6],"of":[7,21,62,123,140,156,187,197],"human":[8],"life":[9],"and":[10,16,27,120,142,161,173,185,206],"transformed":[11],"how":[12],"people":[13,106],"live,":[14],"work,":[15],"interact.":[17],"However,":[18,111],"the":[19,37,40,85,88,95,98,117,130,137,143,153,162,183,195,203],"development":[20,184],"AI":[22,41,89,99,124,131,141,157,198],"also":[23,114],"poses":[24],"potential":[25,109,118,138,163,204],"risks":[26,119,164,205],"ethical":[28,121,146,180,207],"concerns.":[29,208],"In":[30,148],"this":[31],"report,":[32],"we":[33,53],"aim":[34],"to":[35,83,178,192],"analyze":[36,84],"sentiment":[38,86,96],"toward":[39,87],"industry":[42,100,132,174],"using":[43],"hybrid":[44,78],"natural":[45,79],"language":[46,80],"processing":[47,81],"techniques.":[48],"To":[49],"achieve":[50],"our":[51,150],"aim,":[52],"propose":[54],"a":[55,60],"model":[56],"that":[57,94,171,194],"draws":[58],"upon":[59],"survey":[61],"related":[63],"work.":[64],"Data":[65],"collection":[66],"involves":[67],"gathering":[68],"user-generated":[69],"data":[70],"from":[71],"social":[72],"media":[73],"platforms.":[74],"We":[75,169],"then":[76],"use":[77,186],"techniques":[82],"industry.":[90],"Our":[91],"analysis":[92,151],"reveals":[93],"towards":[97],"is":[101],"generally":[102],"positive,":[103],"with":[104,166],"many":[105],"recognizing":[107],"its":[108,167],"benefits.":[110],"there":[112],"are":[113,199],"concerns":[115,135],"about":[116,136],"implications":[122],"development.":[125,168],"Some":[126],"leading":[127],"figures":[128],"in":[129],"have":[133],"expressed":[134],"misuse":[139],"need":[144],"for":[145,182],"guidelines.":[147],"conclusion,":[149],"highlights":[152],"transformative":[154],"effects":[155],"on":[158],"industries":[160],"associated":[165],"recommend":[170],"policymakers":[172],"leaders":[175],"work":[176],"together":[177],"develop":[179],"guidelines":[181],"AI.":[188],"This":[189],"will":[190],"help":[191],"ensure":[193],"benefits":[196],"maximized":[200],"while":[201],"minimizing":[202]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
