{"id":"https://openalex.org/W4385573265","doi":"https://doi.org/10.18653/v1/2022.wanlp-1.44","title":"Benchmarking transfer learning approaches for sentiment analysis of Arabic dialect","display_name":"Benchmarking transfer learning approaches for sentiment analysis of Arabic dialect","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4385573265","doi":"https://doi.org/10.18653/v1/2022.wanlp-1.44"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2022.wanlp-1.44","doi":"https://doi.org/10.18653/v1/2022.wanlp-1.44","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.wanlp-1.44","pdf_url":"https://aclanthology.org/2022.wanlp-1.44.pdf","source":{"id":"https://openalex.org/S7407085968","display_name":"Arabic Natural Language Processing Workshop (WANLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2022.wanlp-1.44.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5076703046","display_name":"Emna Fsih","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Emna Fsih","raw_affiliation_strings":["ANLP Research Group / Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ANLP Research Group / Sfax, Tunisia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5068005332","display_name":"Sam\u00e9h Kchaou","orcid":"https://orcid.org/0000-0003-4674-7671","observed_orcids":["https://orcid.org/0000-0003-4674-7671"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Sameh Kchaou","raw_affiliation_strings":["ANLP Research Group / Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ANLP Research Group / Sfax, Tunisia","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011305430","display_name":"Rahma Boujelbane","orcid":"https://orcid.org/0000-0003-2314-6064","observed_orcids":["https://orcid.org/0000-0003-2314-6064"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Rahma Boujelbane","raw_affiliation_strings":["ANLP Research Group / Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ANLP Research Group / Sfax, Tunisia","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5001984598","display_name":"Lamia Hadrich Belguith","orcid":"https://orcid.org/0000-0002-5063-9246","observed_orcids":["https://orcid.org/0000-0002-5063-9246"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lamia Hadrich-Belguith","raw_affiliation_strings":["ANLP Research Group / Sfax, Tunisia"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"ANLP Research Group / Sfax, Tunisia","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.9669,"has_fulltext":true,"cited_by_count":8,"citation_normalized_percentile":{"value":0.79227456,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"431","last_page":"435"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":1.0,"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":1.0,"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/T10028","display_name":"Topic Modeling","score":9.999999747378752e-05,"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.0,"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/sentiment-analysis","display_name":"sentiment analysis","score":0.8339999914169312},{"id":"https://openalex.org/keywords/arabic-dialects","display_name":"Arabic dialects","score":0.9940000176429749},{"id":"https://openalex.org/keywords/transfer-learning","display_name":"transfer learning","score":0.9779999852180481},{"id":"https://openalex.org/keywords/few-shot-learning","display_name":"few-shot learning","score":0.906000018119812},{"id":"https://openalex.org/keywords/sentence-transformers","display_name":"Sentence Transformers","score":0.5550000071525574},{"id":"https://openalex.org/keywords/camelbert","display_name":"CAMeLBERT","score":0.9470000267028809},{"id":"https://openalex.org/keywords/low-resource-languages","display_name":"low-resource languages","score":0.5659999847412109},{"id":"https://openalex.org/keywords/social-media-text","display_name":"social media text","score":0.6480000019073486}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7551522254943848},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6189993023872375},{"id":"https://openalex.org/C169903167","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Test set","level":2,"score":0.607839822769165},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5977679491043091},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.5693244934082031},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5649861097335815},{"id":"https://openalex.org/C150899416","wikidata":"https://www.wikidata.org/wiki/Q1820378","display_name":"Transfer of learning","level":2,"score":0.5457649827003479},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5273393392562866},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5163044333457947},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.4673730731010437},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4439533054828644},{"id":"https://openalex.org/C2777267654","wikidata":"https://www.wikidata.org/wiki/Q3519023","display_name":"Test (biology)","level":2,"score":0.4345175325870514},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4235588610172272},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3354654312133789},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10221198201179504},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"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/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0},{"id":"https://openalex.org/C162853370","wikidata":"https://www.wikidata.org/wiki/Q39809","display_name":"Marketing","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2022.wanlp-1.44","doi":"https://doi.org/10.18653/v1/2022.wanlp-1.44","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.wanlp-1.44","pdf_url":"https://aclanthology.org/2022.wanlp-1.44.pdf","source":{"id":"https://openalex.org/S7407085968","display_name":"Arabic Natural Language Processing Workshop (WANLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2022.wanlp-1.44","doi":"https://doi.org/10.18653/v1/2022.wanlp-1.44","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/2022.wanlp-1.44","pdf_url":"https://aclanthology.org/2022.wanlp-1.44.pdf","source":{"id":"https://openalex.org/S7407085968","display_name":"Arabic Natural Language Processing Workshop (WANLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"display_name":"Quality education","id":"https://metadata.un.org/sdg/4","score":0.6200000047683716}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385573265.pdf","grobid_xml":"https://content.openalex.org/works/W4385573265.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W2896457183","https://openalex.org/W2970641574","https://openalex.org/W2995322030","https://openalex.org/W3031208816","https://openalex.org/W3032746405","https://openalex.org/W3045210825","https://openalex.org/W3119989085","https://openalex.org/W3134155512","https://openalex.org/W3155561744","https://openalex.org/W3156324355","https://openalex.org/W3176142035","https://openalex.org/W4287548279"],"related_works":["https://openalex.org/W4385567174","https://openalex.org/W4308981845","https://openalex.org/W6939476248","https://openalex.org/W4389358973","https://openalex.org/W7140103456","https://openalex.org/W7166594916","https://openalex.org/W4385572935","https://openalex.org/W7166594779","https://openalex.org/W4385573054","https://openalex.org/W4389518352"],"abstract_inverted_index":{"Arabic":[0],"has":[1,21],"a":[2,88],"widely":[3],"varying":[4],"collection":[5],"of":[6,10,13,18,32,41,82],"dialects.With":[7],"the":[8,11,16,39,83,117,134],"explosion":[9],"use":[12],"social":[14],"networks,":[15],"volume":[17],"written":[19],"texts":[20],"remarkably":[22],"increased.Most":[23],"users":[24],"express":[25],"themselves":[26],"using":[27],"their":[28,78],"own":[29],"dialect.Unfortunately,":[30],"many":[31],"these":[33],"dialects":[34],"remain":[35],"under-studied":[36],"due":[37],"to":[38,86],"scarcity":[40],"resources.Researchers":[42],"and":[43,68,106,112,122,128,133,141,147],"industry":[44],"practitioners":[45],"are":[46],"increasingly":[47],"interested":[48],"in":[49],"analyzing":[50],"users'":[51],"sentiments.In":[52],"this":[53,74,97],"context,":[54],"several":[55],"approaches":[56],"have":[57],"been":[58],"proposed,":[59],"namely:":[60],"traditional":[61],"machine":[62],"learning,":[63],"deep":[64],"learning":[65,67,72],"transfer":[66],"more":[69],"recently":[70],"few-shot":[71],"approaches.In":[73],"work,":[75],"we":[76],"compare":[77],"efficiency":[79],"as":[80],"part":[81],"NADI":[84],"competition":[85],"develop":[87],"country-level":[89],"sentiment":[90],"analysis":[91],"model.Three":[92],"models":[93],"were":[94],"beneficial":[95],"for":[96],"sub-task:":[98],"The":[99],"first":[100],"based":[101,119,136],"on":[102,109,114,120,125,130,137,144,149],"Sentence":[103],"Transformer":[104],"(ST)":[105],"achieve":[107,123,142],"43.23%":[108],"DEV":[110,126,145],"set":[111,127,132,146],"42.33%":[113],"TEST":[115,131,150],"set,":[116],"second":[118],"CAMeLBERT":[121],"54.00%":[124],"43.11%":[129],"third":[135],"multi-dialect":[138],"BERT":[139],"model":[140],"66.72%":[143],"39.69%":[148],"set.":[151]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2023-08-05T00:00:00"}
