{"id":"https://openalex.org/W4382680318","doi":"https://doi.org/10.1145/3605889","title":"Arabic ChatGPT Tweets Classification Using RoBERTa and BERT Ensemble Model","display_name":"Arabic ChatGPT Tweets Classification Using RoBERTa and BERT Ensemble Model","publication_year":2023,"publication_date":"2023-06-30","ids":{"openalex":"https://openalex.org/W4382680318","doi":"https://doi.org/10.1145/3605889"},"language":"en","primary_location":{"id":"doi:10.1145/3605889","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3605889","pdf_url":null,"source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","raw_type":"journal-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/A5047043390","display_name":"Muhammad Mujahid","orcid":"https://orcid.org/0009-0005-5751-5528"},"institutions":[{"id":"https://openalex.org/I4210102737","display_name":"Khwaja Fareed University of Engineering and Information Technology","ror":"https://ror.org/0161dyt30","country_code":"PK","type":"education","lineage":["https://openalex.org/I4210102737"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Muhammad Mujahid","raw_affiliation_strings":["Department of Computer Science, Khwaja Fareed University of Engineering and Information Technology, Pakistan"],"raw_orcid":"https://orcid.org/0009-0005-5751-5528","affiliations":[{"raw_affiliation_string":"Department of Computer Science, Khwaja Fareed University of Engineering and Information Technology, Pakistan","institution_ids":["https://openalex.org/I4210102737"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070702816","display_name":"Khadija Kanwal","orcid":"https://orcid.org/0009-0001-2300-9636"},"institutions":[{"id":"https://openalex.org/I4210126226","display_name":"The Women University Multan","ror":"https://ror.org/035ggvj17","country_code":"PK","type":"education","lineage":["https://openalex.org/I4210126226"]}],"countries":["PK"],"is_corresponding":false,"raw_author_name":"Khadija Kanwal","raw_affiliation_strings":["Institute of CS and IT, The Women University Multan, Pakistan"],"raw_orcid":"https://orcid.org/0009-0001-2300-9636","affiliations":[{"raw_affiliation_string":"Institute of CS and IT, The Women University Multan, Pakistan","institution_ids":["https://openalex.org/I4210126226"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5058941449","display_name":"Furqan Rustam","orcid":"https://orcid.org/0000-0001-8403-1047"},"institutions":[{"id":"https://openalex.org/I100930933","display_name":"University College Dublin","ror":"https://ror.org/05m7pjf47","country_code":"IE","type":"education","lineage":["https://openalex.org/I100930933"]}],"countries":["IE"],"is_corresponding":false,"raw_author_name":"Furqan Rustam","raw_affiliation_strings":["School of Computer Science, University College Dublin, Ireland"],"raw_orcid":"https://orcid.org/0000-0001-8403-1047","affiliations":[{"raw_affiliation_string":"School of Computer Science, University College Dublin, Ireland","institution_ids":["https://openalex.org/I100930933"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5057627035","display_name":"Wajdi Aljedaani","orcid":"https://orcid.org/0000-0002-6700-719X"},"institutions":[{"id":"https://openalex.org/I123534392","display_name":"University of North Texas","ror":"https://ror.org/00v97ad02","country_code":"US","type":"education","lineage":["https://openalex.org/I123534392"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Wajdi Aljedaani","raw_affiliation_strings":["University of North Texas, USA"],"raw_orcid":"https://orcid.org/0000-0002-6700-719X","affiliations":[{"raw_affiliation_string":"University of North Texas, USA","institution_ids":["https://openalex.org/I123534392"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5074629800","display_name":"Imran Ashraf","orcid":"https://orcid.org/0000-0002-8271-6496"},"institutions":[{"id":"https://openalex.org/I55240360","display_name":"Yeungnam University","ror":"https://ror.org/05yc6p159","country_code":"KR","type":"education","lineage":["https://openalex.org/I55240360"]}],"countries":["KR"],"is_corresponding":false,"raw_author_name":"Imran Ashraf","raw_affiliation_strings":["Department of Information and Communication Engineering, Yeungnam University, Korea"],"raw_orcid":"https://orcid.org/0000-0002-8271-6496","affiliations":[{"raw_affiliation_string":"Department of Information and Communication Engineering, Yeungnam University, Korea","institution_ids":["https://openalex.org/I55240360"]}]}],"institutions":[],"countries_distinct_count":4,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":7.1791,"has_fulltext":false,"cited_by_count":44,"citation_normalized_percentile":{"value":0.97740227,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":100},"biblio":{"volume":"22","issue":"8","first_page":"1","last_page":"23"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9979000091552734,"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/T10028","display_name":"Topic Modeling","score":0.9979000091552734,"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/T12128","display_name":"AI in Service Interactions","score":0.9962000250816345,"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/T11636","display_name":"Artificial Intelligence in Healthcare and Education","score":0.9952999949455261,"subfield":{"id":"https://openalex.org/subfields/2718","display_name":"Health Informatics"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7913353443145752},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6694030165672302},{"id":"https://openalex.org/keywords/python","display_name":"Python (programming language)","score":0.6367325782775879},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.636685848236084},{"id":"https://openalex.org/keywords/punctuation","display_name":"Punctuation","score":0.6253737211227417},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6023841500282288},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.5701062679290771},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.47176364064216614},{"id":"https://openalex.org/keywords/chatbot","display_name":"Chatbot","score":0.4640914797782898},{"id":"https://openalex.org/keywords/preprocessor","display_name":"Preprocessor","score":0.42753979563713074},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32885730266571045},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.32386213541030884},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.16099563241004944}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7913353443145752},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6694030165672302},{"id":"https://openalex.org/C519991488","wikidata":"https://www.wikidata.org/wiki/Q28865","display_name":"Python (programming language)","level":2,"score":0.6367325782775879},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.636685848236084},{"id":"https://openalex.org/C540372491","wikidata":"https://www.wikidata.org/wiki/Q82622","display_name":"Punctuation","level":2,"score":0.6253737211227417},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6023841500282288},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.5701062679290771},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.47176364064216614},{"id":"https://openalex.org/C2779041454","wikidata":"https://www.wikidata.org/wiki/Q870780","display_name":"Chatbot","level":2,"score":0.4640914797782898},{"id":"https://openalex.org/C34736171","wikidata":"https://www.wikidata.org/wiki/Q918333","display_name":"Preprocessor","level":2,"score":0.42753979563713074},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32885730266571045},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.32386213541030884},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.16099563241004944},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3605889","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3605889","pdf_url":null,"source":{"id":"https://openalex.org/S4306421405","display_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","issn_l":"2375-4699","issn":["2375-4699","2375-4702"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319798","host_organization_name":"Association for Computing Machinery","host_organization_lineage":["https://openalex.org/P4310319798"],"host_organization_lineage_names":["Association for Computing Machinery"],"type":"journal"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"ACM Transactions on Asian and Low-Resource Language Information Processing","raw_type":"journal-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8299999833106995}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":50,"referenced_works":["https://openalex.org/W1965606641","https://openalex.org/W1988195734","https://openalex.org/W1990239322","https://openalex.org/W2014545475","https://openalex.org/W2074975950","https://openalex.org/W2168231245","https://openalex.org/W2335272770","https://openalex.org/W2341366677","https://openalex.org/W2409135246","https://openalex.org/W2583531327","https://openalex.org/W2808282688","https://openalex.org/W2901922204","https://openalex.org/W2947168485","https://openalex.org/W2964335273","https://openalex.org/W2965373594","https://openalex.org/W2977526300","https://openalex.org/W2994856814","https://openalex.org/W2999286261","https://openalex.org/W3014675721","https://openalex.org/W3022540180","https://openalex.org/W3027572503","https://openalex.org/W3033291431","https://openalex.org/W3034266838","https://openalex.org/W3112103703","https://openalex.org/W3119546299","https://openalex.org/W3121384227","https://openalex.org/W3131676280","https://openalex.org/W3136363192","https://openalex.org/W3153642904","https://openalex.org/W3181034584","https://openalex.org/W3195446119","https://openalex.org/W3199146084","https://openalex.org/W3203679867","https://openalex.org/W4281650121","https://openalex.org/W4293217217","https://openalex.org/W4297731784","https://openalex.org/W4311430511","https://openalex.org/W4313294616","https://openalex.org/W4313300397","https://openalex.org/W4313569896","https://openalex.org/W4313648835","https://openalex.org/W4315784077","https://openalex.org/W4316466456","https://openalex.org/W4316658248","https://openalex.org/W4318931874","https://openalex.org/W4319065746","https://openalex.org/W4319083882","https://openalex.org/W4385572935","https://openalex.org/W4385573265","https://openalex.org/W6639497327"],"related_works":["https://openalex.org/W4383501580","https://openalex.org/W2936002343","https://openalex.org/W4214931137","https://openalex.org/W4313813117","https://openalex.org/W4382052417","https://openalex.org/W3192088754","https://openalex.org/W2188883480","https://openalex.org/W1592364192","https://openalex.org/W656840002","https://openalex.org/W1605117403"],"abstract_inverted_index":{"ChatGPT":[0,25,44,63,82,94],"OpenAI,":[1],"a":[2,8,30,149,259,287,299,306],"large-language":[3],"chatbot":[4],"model,":[5],"has":[6,137],"gained":[7],"lot":[9],"of":[10,33,151,232,280,324,353,380],"attention":[11],"due":[12,319],"to":[13,29,70,86,236,265,302,320,336],"its":[14,74],"popularity":[15],"and":[16,37,50,65,72,76,91,100,111,143,173,181,191,199,207,240,251,283,305,340,343,372],"impressive":[17],"performance":[18,180,379],"in":[19,327],"many":[20],"natural":[21],"language":[22],"processing":[23],"tasks.":[24],"produces":[26],"superior":[27],"answers":[28],"wide":[31],"range":[32],"real-world":[34],"human":[35],"questions":[36],"generates":[38],"human-like":[39],"text.":[40],"The":[41,96,269,378],"new":[42],"OpenAI":[43],"technology":[45],"may":[46],"have":[47,57,211],"some":[48],"strengths":[49],"weaknesses":[51],"at":[52],"this":[53],"early":[54,59],"stage.":[55],"Users":[56],"reported":[58],"opinions":[60,90],"about":[61,93,132],"the":[62,81,103,118,158,178,215,221,230,256,277,281,321,333,345,360,381],"features,":[64],"their":[66],"feedback":[67],"is":[68,98,263,273,384],"essential":[69],"recognize":[71],"fix":[73],"shortcomings":[75],"issues.":[77],"This":[78,242],"study":[79,243],"uses":[80],"tweets":[83,154,186],"Arabic":[84,105,123,133],"dataset":[85,97],"automatically":[87,254],"find":[88],"user":[89],"sentiments":[92],"technology.":[95],"preprocessed":[99],"labeled":[101],"using":[102,157,163,286],"TextBlob":[104],"Python":[106,161,233],"library":[107,162],"into":[108,189],"positive,":[109],"negative,":[110],"neutral":[112,376],"tweets.":[113,257,377],"Despite":[114],"extensive":[115],"works":[116],"for":[117,310,375],"English":[119],"language,":[120],"languages":[121],"like":[122],"are":[124,187,227,351],"less":[125],"studied":[126],"regarding":[127],"tweet":[128,134],"analysis.":[129],"Existing":[130],"literature":[131],"sentiment":[135],"analysis":[136],"mainly":[138],"focused":[139],"on":[140,214,369],"machine":[141],"learning":[142,145],"deep":[144],"models.":[146,390],"We":[147],"collected":[148],"total":[150],"27,780":[152],"unstructured":[153,185],"from":[155,315],"Twitter":[156],"Tweepy":[159],"SNscrape":[160],"various":[164],"hash-tags":[165],"such":[166,247],"as":[167,248,298],"#":[168],"Chat-GPT,":[169],"#OpenAI,":[170],"#Chatbot,":[171],"Chat-GPT3,":[172],"so":[174],"on.":[175],"To":[176],"enhance":[177,237],"model\u2019s":[179],"reduce":[182,341],"computational":[183,222],"complexity,":[184],"converted":[188],"structured":[190],"normalized":[192],"forms.":[193],"Tweets":[194],"contain":[195],"missing":[196],"values,":[197],"URL":[198],"HTML":[200],"tags,":[201],"stop":[202],"words,":[203],"punctuation,":[204],"diacritics,":[205],"elongations,":[206],"numeric":[208],"values":[209],"that":[210,253,359],"no":[212],"impact":[213],"model":[216,262,272,363,383],"performance;":[217],"hence,":[218],"these":[219,225],"increase":[220],"cost.":[223],"So,":[224],"steps":[226],"removed":[228],"with":[229,294],"help":[231],"preprocessing":[234],"libraries":[235],"text":[238,328],"quality":[239],"consistency.":[241],"adopts":[244],"Transformer-based":[245],"models":[246,285,318,326,331,335,350],"RoBERTa,":[249],"XLNet,":[250],"DistilBERT":[252],"classify":[255],"Additionally,":[258],"hybrid":[260,271,362],"transformer-based":[261],"proposed":[264,270,361,382],"obtain":[266],"better":[267,386],"results.":[268],"developed":[274],"by":[275],"combining":[276],"hidden":[278,300],"outputs":[279],"RoBERTA":[282],"BERT":[284],"concatenation":[288],"layer,":[289],"then":[290],"adding":[291],"dense":[292],"layers":[293],"\u201cRelu\u201d":[295],"activation":[296,308],"employed":[297],"layer":[301],"create":[303],"non-linearity":[304],"\u201csoftmax\u201d":[307],"function":[309],"multiclass":[311],"classification.":[312,329],"They":[313],"differ":[314],"existing":[316,388],"state-of-the-art":[317,349,389],"enhanced":[322,344],"capabilities":[323],"both":[325],"Hybrid":[330],"combine":[332],"different":[334],"make":[337],"accurate":[338,355],"predictions":[339],"bias":[342],"overall":[346],"results,":[347],"while":[348],"incapable":[352],"making":[354],"predictions.":[356],"Experiments":[357],"show":[358],"achieves":[364],"96.02%":[365],"accuracy,":[366],"100%":[367],"precision":[368],"negative":[370],"tweets,":[371],"99%":[373],"recall":[374],"far":[385],"than":[387]},"counts_by_year":[{"year":2026,"cited_by_count":3},{"year":2025,"cited_by_count":12},{"year":2024,"cited_by_count":22},{"year":2023,"cited_by_count":7}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}
