{"id":"https://openalex.org/W7101600730","doi":"https://doi.org/10.48550/arxiv.2510.23585","title":"Hope Speech Detection in Social Media English Corpora: Performance of Traditional and Transformer Models","display_name":"Hope Speech Detection in Social Media English Corpora: Performance of Traditional and Transformer Models","publication_year":2025,"publication_date":"2025-10-27","ids":{"openalex":"https://openalex.org/W7101600730","doi":"https://doi.org/10.48550/arxiv.2510.23585"},"language":"en","primary_location":{"id":"pmh:oai:arXiv.org:2510.23585","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.23585","pdf_url":"https://arxiv.org/pdf/2510.23585","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"volume":null,"type":"preprint","indexed_in":["arxiv","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://arxiv.org/pdf/2510.23585","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5123638713","display_name":"Luis Ramos","orcid":"https://orcid.org/0009-0008-5586-6668","observed_orcids":["https://orcid.org/0009-0008-5586-6668"]},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Ramos, Luis","raw_affiliation_strings":["Instituto Polit\u00e9cnico Nacional , Centro de Investigaci\u00f3n en Computaci\u00f3n , Mexico City , Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto Polit\u00e9cnico Nacional , Centro de Investigaci\u00f3n en Computaci\u00f3n , Mexico City , Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5055414768","display_name":"Hiram Calvo","orcid":"https://orcid.org/0000-0003-2836-2102","observed_orcids":["https://orcid.org/0000-0003-2836-2102"]},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Calvo, Hiram","raw_affiliation_strings":["Instituto Polit\u00e9cnico Nacional , Centro de Investigaci\u00f3n en Computaci\u00f3n , Mexico City , Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto Polit\u00e9cnico Nacional , Centro de Investigaci\u00f3n en Computaci\u00f3n , Mexico City , Mexico","institution_ids":["https://openalex.org/I59361560"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061018630","display_name":"Olga Kolesnikova","orcid":"https://orcid.org/0000-0002-1307-1647","observed_orcids":["https://orcid.org/0000-0002-1307-1647"]},"institutions":[{"id":"https://openalex.org/I59361560","display_name":"Instituto Polit\u00e9cnico Nacional","ror":"https://ror.org/059sp8j34","country_code":"MX","type":"education","lineage":["https://openalex.org/I59361560"]}],"countries":["MX"],"is_corresponding":false,"raw_author_name":"Kolesnikova, Olga","raw_affiliation_strings":["Instituto Polit\u00e9cnico Nacional , Centro de Investigaci\u00f3n en Computaci\u00f3n , Mexico City , Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Instituto Polit\u00e9cnico Nacional , Centro de Investigaci\u00f3n en Computaci\u00f3n , Mexico City , Mexico","institution_ids":["https://openalex.org/I59361560"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I59361560"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9648000001907349,"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":0.9648000001907349,"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":0.01510000042617321,"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/T12488","display_name":"Mental Health via Writing","score":0.014100000262260437,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/hope-speech-detection","display_name":"hope speech detection","score":0.9919999837875366},{"id":"https://openalex.org/keywords/social-media-text","display_name":"social media text","score":0.7059999704360962},{"id":"https://openalex.org/keywords/transformer","display_name":"transformer models","score":0.6660000085830688},{"id":"https://openalex.org/keywords/traditional-machine-learning","display_name":"traditional machine learning","score":0.6119999885559082},{"id":"https://openalex.org/keywords/svm","display_name":"SVM","score":0.5249999761581421},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"logistic regression","score":0.9190000295639038},{"id":"https://openalex.org/keywords/naive-bayes","display_name":"naive Bayes","score":0.8460000157356262},{"id":"https://openalex.org/keywords/small-datasets","display_name":"small datasets","score":0.5170000195503235},{"id":"https://openalex.org/keywords/goal-directed-behavior","display_name":"goal-directed behavior","score":0.6959999799728394}],"concepts":[{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.7361999750137329},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.6407999992370605},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6136999726295471},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5795999765396118},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.49950000643730164},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4966999888420105},{"id":"https://openalex.org/C100660578","wikidata":"https://www.wikidata.org/wiki/Q18733","display_name":"Recall","level":2,"score":0.49070000648498535},{"id":"https://openalex.org/C81669768","wikidata":"https://www.wikidata.org/wiki/Q2359161","display_name":"Precision and recall","level":2,"score":0.4900999963283539},{"id":"https://openalex.org/C204201278","wikidata":"https://www.wikidata.org/wiki/Q1332614","display_name":"Voice activity detection","level":3,"score":0.48399999737739563},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.4300000071525574},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.3856000006198883},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3407000005245209},{"id":"https://openalex.org/C23224414","wikidata":"https://www.wikidata.org/wiki/Q176769","display_name":"Hidden Markov model","level":2,"score":0.3089999854564667},{"id":"https://openalex.org/C101738243","wikidata":"https://www.wikidata.org/wiki/Q786435","display_name":"Autoencoder","level":3,"score":0.3012000024318695},{"id":"https://openalex.org/C61328038","wikidata":"https://www.wikidata.org/wiki/Q3358061","display_name":"Speech processing","level":2,"score":0.27239999175071716},{"id":"https://openalex.org/C166955791","wikidata":"https://www.wikidata.org/wiki/Q629579","display_name":"Macro","level":2,"score":0.26669999957084656},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.2597000002861023},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.2583000063896179},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.2556000053882599},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.25380000472068787}],"mesh":[],"locations_count":2,"locations":[{"id":"pmh:oai:arXiv.org:2510.23585","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.23585","pdf_url":"https://arxiv.org/pdf/2510.23585","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},{"id":"doi:10.48550/arxiv.2510.23585","doi":"https://doi.org/10.48550/arxiv.2510.23585","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2510.23585","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Preprint"}],"best_oa_location":{"id":"pmh:oai:arXiv.org:2510.23585","doi":null,"is_oa":true,"landing_page_url":"http://arxiv.org/abs/2510.23585","pdf_url":"https://arxiv.org/pdf/2510.23585","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"is_oa":true,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"text"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W7101600730.pdf","grobid_xml":"https://content.openalex.org/works/W7101600730.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W3129651031","https://openalex.org/W4378603584","https://openalex.org/W7104557885","https://openalex.org/W7118013133","https://openalex.org/W4285257642","https://openalex.org/W3156677371","https://openalex.org/W7083312474","https://openalex.org/W4285274598","https://openalex.org/W7128959938","https://openalex.org/W4378571969"],"abstract_inverted_index":{"The":[0],"identification":[1],"of":[2,18,63,87,91,95,99,123],"hope":[3,41,124,132],"speech":[4,42,133],"has":[5],"become":[6],"a":[7,38,53,61],"promised":[8],"NLP":[9],"task,":[10],"considering":[11],"the":[12,81],"need":[13],"to":[14,125],"detect":[15,119],"motivational":[16],"expressions":[17],"agency":[19],"and":[20,34,47,56,71,101,129,139],"goal-directed":[21],"behaviour":[22],"on":[23],"social":[24],"media":[25],"platforms.":[26],"This":[27],"proposal":[28],"evaluates":[29],"traditional":[30,111],"machine":[31,112],"learning":[32,113],"models":[33,77,114],"fine-tuned":[35],"transformers":[36,138],"for":[37],"previously":[39],"split":[40],"dataset":[43],"as":[44],"train,":[45],"development":[46,51],"test":[48],"set.":[49],"On":[50],"test,":[52],"linear-kernel":[54],"SVM":[55,65],"logistic":[57],"regression":[58],"both":[59],"reached":[60,69],"macro-F1":[62],"0.78;":[64],"with":[66],"RBF":[67],"kernel":[68],"0.77,":[70],"Na\u00efve":[72],"Bayes":[73],"hit":[74],"0.75.":[75],"Transformer":[76],"delivered":[78],"better":[79,143],"results,":[80],"best":[82],"model":[83],"achieved":[84],"weighted":[85,89,93],"precision":[86,128],"0.82,":[88],"recall":[90,130],"0.80,":[92],"F1":[94,98],"0.79,":[96,100],"macro":[97],"0.80":[102],"accuracy.":[103],"These":[104],"results":[105],"suggest":[106],"that":[107,136],"while":[108],"optimally":[109],"configured":[110],"remain":[115],"agile,":[116],"transformer":[117],"architectures":[118],"some":[120],"subtle":[121],"semantics":[122],"achieve":[126],"higher":[127],"in":[131,144],"detection,":[134],"suggesting":[135],"larges":[137],"LLMs":[140],"could":[141],"perform":[142],"small":[145],"datasets.":[146]},"counts_by_year":[],"updated_date":"2026-10-28T10:33:24.094632","created_date":"2025-10-29T00:00:00"}