{"id":"https://openalex.org/W7138256392","doi":"https://doi.org/10.48550/arxiv.2603.13655","title":"Privacy Preserving Topic-wise Sentiment Analysis of the Iran Israel USA Conflict Using Federated Transformer Models","display_name":"Privacy Preserving Topic-wise Sentiment Analysis of the Iran Israel USA Conflict Using Federated Transformer Models","publication_year":2026,"publication_date":"2026-03-13","ids":{"openalex":"https://openalex.org/W7138256392","doi":"https://doi.org/10.48550/arxiv.2603.13655"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2603.13655","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13655","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2603.13655","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5129679105","display_name":"Md Saiful Islam","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Islam, Md Saiful","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5082710448","display_name":"Tanjim Taharat Aurpa","orcid":"https://orcid.org/0000-0003-1471-1316"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aurpa, Tanjim Taharat","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5125576651","display_name":"Sharad Hasan","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hasan, Sharad","raw_affiliation_strings":[],"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5102975713","display_name":"Farzana Akter","orcid":"https://orcid.org/0000-0003-3017-8742"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Akter, Farzana","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5129679105"],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"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":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.3625999987125397,"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":0.3625999987125397,"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":0.1623000055551529,"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/T11147","display_name":"Misinformation and Its Impacts","score":0.05050000175833702,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.8586999773979187},{"id":"https://openalex.org/keywords/latent-dirichlet-allocation","display_name":"Latent Dirichlet allocation","score":0.7558000087738037},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5555999875068665},{"id":"https://openalex.org/keywords/public-opinion","display_name":"Public opinion","score":0.5331000089645386},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.47760000824928284},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.47440001368522644}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.8586999773979187},{"id":"https://openalex.org/C500882744","wikidata":"https://www.wikidata.org/wiki/Q269236","display_name":"Latent Dirichlet allocation","level":3,"score":0.7558000087738037},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7085000276565552},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5555999875068665},{"id":"https://openalex.org/C134698397","wikidata":"https://www.wikidata.org/wiki/Q17946","display_name":"Public opinion","level":3,"score":0.5331000089645386},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.47760000824928284},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.47440001368522644},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4666999876499176},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.45489999651908875},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.44909998774528503},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.4156000018119812},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.31850001215934753},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.3041999936103821},{"id":"https://openalex.org/C18762648","wikidata":"https://www.wikidata.org/wiki/Q42213","display_name":"Work (physics)","level":2,"score":0.2939000129699707},{"id":"https://openalex.org/C162446236","wikidata":"https://www.wikidata.org/wiki/Q653137","display_name":"Content analysis","level":2,"score":0.28839999437332153},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.2865000069141388},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.28299999237060547},{"id":"https://openalex.org/C2992525071","wikidata":"https://www.wikidata.org/wiki/Q50818671","display_name":"Federated learning","level":2,"score":0.2711000144481659}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2603.13655","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13655","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"article"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2603.13655","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2603.13655","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"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":null,"license_id":null,"version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6464876532554626}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,65,165,225],"recent":[1],"escalation":[2],"of":[3],"the":[4,52,120,146,219],"Iran":[5,53],"Israel":[6,54],"USA":[7,55],"conflict":[8,56],"in":[9,238],"2026":[10],"has":[11],"triggered":[12],"widespread":[13],"global":[14,40,48],"discussions":[15,34],"across":[16],"social":[17],"media":[18],"platforms.":[19],"As":[20],"people":[21],"increasingly":[22],"use":[23],"these":[24,33],"platforms":[25],"for":[26,162],"expressing":[27],"opinions,":[28],"analyzing":[29],"public":[30,41,49,69],"sentiment":[31,50,82,122,163,204],"from":[32,61,101],"can":[35],"provide":[36],"valuable":[37],"insights":[38],"into":[39,171],"perception.":[42],"This":[43],"study":[44],"aims":[45],"to":[46,68,108,130,139,145,176,195],"analyze":[47],"regarding":[51],"by":[57,72,180],"mining":[58],"user-generated":[59],"comments":[60,98],"YouTube":[62,97],"news":[63,104],"channels.":[64],"work":[66],"contributes":[67],"opinion":[70],"analysis":[71,83],"introducing":[73],"a":[74,172,239],"privacy":[75],"preserving":[76,181,233],"framework":[77],"that":[78,209],"combines":[79],"topic":[80],"wise":[81],"with":[84,222],"modern":[85],"deep":[86],"learning":[87,174,227],"techniques":[88,190],"and":[89,106,111,124,157,199,214],"Federated":[90],"Learning.":[91],"To":[92],"achieve":[93],"this,":[94],"approximately":[95],"19,000":[96],"were":[99,116,159,193],"collected":[100],"major":[102],"international":[103],"channels":[105],"preprocessed":[107],"remove":[109],"noise":[110],"normalize":[112],"text.":[113],"Sentiment":[114],"labels":[115],"initially":[117],"generated":[118],"using":[119,191],"VADER":[121],"analyzer":[123],"later":[125],"validated":[126],"through":[127],"manual":[128],"inspection":[129],"improve":[131],"reliability.":[132],"Latent":[133],"Dirichlet":[134],"Allocation":[135],"(LDA)":[136],"was":[137,168],"applied":[138,194],"identify":[140,200],"key":[141],"discussion":[142],"topics":[143],"related":[144],"conflict.":[147],"Several":[148],"transformer-based":[149],"models,":[150],"including":[151],"BERT,":[152],"RoBERTa,":[153],"XLNet,":[154],"DistilBERT,":[155],"ModernBERT,":[156],"ELECTRA,":[158],"fine":[160],"tuned":[161],"classification.":[164,205],"best-performing":[166],"model":[167,197],"further":[169],"integrated":[170],"federated":[173,226],"environment":[175],"enable":[177],"distributed":[178],"training":[179],"user":[182],"data":[183],"privacy.":[184],"Additionally,":[185],"Explainable":[186],"Artificial":[187],"Intelligence":[188],"(XAI)":[189],"SHAP":[192],"interpret":[196],"predictions":[198],"influential":[201],"words":[202],"affecting":[203],"Experimental":[206],"results":[207],"demonstrate":[208],"transformer":[210],"models":[211],"perform":[212],"effectively,":[213],"among":[215],"them,":[216],"ELECTRA":[217],"achieved":[218],"best":[220],"performance":[221,231],"91.32%":[223],"accuracy.":[224],"also":[228],"maintained":[229],"strong":[230],"while":[232],"privacy,":[234],"achieving":[235],"89.59%":[236],"accuracy":[237],"two":[240],"client":[241],"configuration.":[242]},"counts_by_year":[],"updated_date":"2026-03-18T06:31:55.123368","created_date":"2026-03-18T00:00:00"}
