{"id":"https://openalex.org/W4406458506","doi":"https://doi.org/10.1109/bigdata62323.2024.10825258","title":"Decoding Narratives: Towards a Classification Analysis for Stereotypical Patterns in Italian News Headlines","display_name":"Decoding Narratives: Towards a Classification Analysis for Stereotypical Patterns in Italian News Headlines","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406458506","doi":"https://doi.org/10.1109/bigdata62323.2024.10825258"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","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/A5093760738","display_name":"Matteo Berta","orcid":null},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":true,"raw_author_name":"Matteo Berta","raw_affiliation_strings":["Politecnico di Torino,DAUIN,Turin,Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino,DAUIN,Turin,Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5061608915","display_name":"Salvatore Greco","orcid":"https://orcid.org/0000-0001-7239-9602"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Salvatore Greco","raw_affiliation_strings":["Politecnico di Torino,DAUIN,Turin,Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino,DAUIN,Turin,Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5115940090","display_name":"Giuseppe Tipaldo","orcid":null},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Giuseppe Tipaldo","raw_affiliation_strings":["Politecnico di Torino,DAUIN,Turin,Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino,DAUIN,Turin,Italy","institution_ids":["https://openalex.org/I177477856"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053742461","display_name":"Tania Cerquitelli","orcid":"https://orcid.org/0000-0002-9039-6226"},"institutions":[{"id":"https://openalex.org/I177477856","display_name":"Polytechnic University of Turin","ror":"https://ror.org/00bgk9508","country_code":"IT","type":"education","lineage":["https://openalex.org/I177477856"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Tania Cerquitelli","raw_affiliation_strings":["Politecnico di Torino,DAUIN,Turin,Italy"],"affiliations":[{"raw_affiliation_string":"Politecnico di Torino,DAUIN,Turin,Italy","institution_ids":["https://openalex.org/I177477856"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5093760738"],"corresponding_institution_ids":["https://openalex.org/I177477856"],"apc_list":null,"apc_paid":null,"fwci":0.3415,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":{"value":0.70033571,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":96,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"5253","last_page":"5262"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12380","display_name":"Authorship Attribution and Profiling","score":0.9926000237464905,"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/T12380","display_name":"Authorship Attribution and Profiling","score":0.9926000237464905,"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/T13718","display_name":"Media Influence and Politics","score":0.9869999885559082,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.98580002784729,"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/decoding-methods","display_name":"Decoding methods","score":0.7854803800582886},{"id":"https://openalex.org/keywords/narrative","display_name":"Narrative","score":0.7451362013816833},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6154592037200928},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.41970115900039673},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.40869683027267456},{"id":"https://openalex.org/keywords/speech-recognition","display_name":"Speech recognition","score":0.32989054918289185},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.26074686646461487},{"id":"https://openalex.org/keywords/telecommunications","display_name":"Telecommunications","score":0.15655392408370972}],"concepts":[{"id":"https://openalex.org/C57273362","wikidata":"https://www.wikidata.org/wiki/Q576722","display_name":"Decoding methods","level":2,"score":0.7854803800582886},{"id":"https://openalex.org/C199033989","wikidata":"https://www.wikidata.org/wiki/Q1318295","display_name":"Narrative","level":2,"score":0.7451362013816833},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6154592037200928},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.41970115900039673},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.40869683027267456},{"id":"https://openalex.org/C28490314","wikidata":"https://www.wikidata.org/wiki/Q189436","display_name":"Speech recognition","level":1,"score":0.32989054918289185},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.26074686646461487},{"id":"https://openalex.org/C76155785","wikidata":"https://www.wikidata.org/wiki/Q418","display_name":"Telecommunications","level":1,"score":0.15655392408370972},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825258","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825258","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W2022213963","https://openalex.org/W2119467284","https://openalex.org/W2487898712","https://openalex.org/W2601065187","https://openalex.org/W2906692653","https://openalex.org/W2952861497","https://openalex.org/W2962772482","https://openalex.org/W3013564570","https://openalex.org/W3044248538","https://openalex.org/W3117696238","https://openalex.org/W3152973264","https://openalex.org/W3161597661","https://openalex.org/W3163637917","https://openalex.org/W4200075749","https://openalex.org/W4205443564","https://openalex.org/W4233098163","https://openalex.org/W4283332711","https://openalex.org/W4285414158","https://openalex.org/W4296050762","https://openalex.org/W4300749016","https://openalex.org/W4304098849","https://openalex.org/W4319878045","https://openalex.org/W4322718191","https://openalex.org/W4328130717","https://openalex.org/W4380988051","https://openalex.org/W4386806248","https://openalex.org/W4394902775","https://openalex.org/W4400373649","https://openalex.org/W4404172767","https://openalex.org/W6662223489","https://openalex.org/W6737947904"],"related_works":["https://openalex.org/W2348886128","https://openalex.org/W2388067091","https://openalex.org/W2367656648","https://openalex.org/W2350200549","https://openalex.org/W2362132076","https://openalex.org/W2965396777","https://openalex.org/W2389168924","https://openalex.org/W2067294484","https://openalex.org/W4280593102","https://openalex.org/W3204019825"],"abstract_inverted_index":{"Media":[0],"headlines":[1,97,138,195],"shape":[2],"our":[3],"initial":[4],"interpretation":[5],"of":[6,56,81,86,115,122,259],"news,":[7],"framing":[8,47],"narratives":[9],"that":[10,236],"influence":[11],"societal":[12],"engagement":[13],"with":[14,64],"political":[15,50,66],"and":[16,25,46,72,83,118,143,149,169,180,189,200,231],"social":[17,190,239],"issues.":[18],"Yet,":[19],"they":[20],"often":[21,175],"rely":[22],"on":[23],"sensationalism":[24],"bias":[26],"to":[27,35,92,111,132,147,197,204,255],"capture":[28],"readers\u2019":[29],"attention.In":[30],"this":[31],"paper,":[32],"we":[33],"aim":[34],"uncover":[36],"distinct":[37,155],"patterns":[38,135,222],"in":[39,202,223,234],"Italian":[40,58],"headline":[41],"composition,":[42],"examining":[43],"how":[44],"language":[45],"vary":[48],"across":[49],"leanings.":[51],"We":[52],"analyze":[53],"a":[54,84,100,108,166,177,256],"dataset":[55],"daily":[57],"newspaper":[59],"articles":[60],"from":[61,210],"two":[62,141,160],"outlets":[63,218,252],"opposing":[65],"perspectives,":[67],"anonymized":[68],"as":[69,227],"Newspaper":[70,73,162,173,193,211],"A":[71,163],"B.":[74],"Our":[75,104],"study":[76],"encompasses":[77],"the":[78,120,159,205],"entire":[79],"set":[80],"news":[82],"subset":[85],"topics":[87,186],"(n":[88],"=":[89,130],"8)":[90],"likely":[91],"contain":[93],"stereotypes":[94],"or":[95],"clickbait":[96],"identified":[98],"using":[99],"Large":[101],"Language":[102],"Model.":[103],"methodology":[105],"combines":[106],"(1)":[107],"lexicometric":[109],"analysis":[110,153],"identify":[112],"characteristic":[113],"words":[114],"each":[116],"newspaper,":[117],"(2)":[119],"training":[121],"an":[123],"accurate":[124],"deep":[125],"learning":[126],"classifier":[127],"(F":[128],"1":[129],"0.84)":[131],"learn":[133],"specific":[134],"for":[136],"categorizing":[137],"into":[139],"these":[140,151,214],"perspectives":[142],"leveraging":[144],"explainability":[145],"techniques":[146],"extract":[148],"interpret":[150],"patterns.Our":[152],"reveals":[154],"tonal":[156,215],"differences":[157],"between":[158],"newspapers:":[161],"generally":[164],"adopts":[165],"more":[167,178,207],"balanced":[168],"nuanced":[170],"approach,":[171],"while":[172],"B":[174],"favors":[176],"direct":[179],"sometimes":[181],"provocative":[182],"style,":[183],"especially":[184],"regarding":[185],"like":[187],"immigration":[188],"justice.":[191],"Additionally,":[192],"B\u2019s":[194],"tend":[196],"be":[198],"brief":[199],"punchy,":[201],"contrast":[203],"longer,":[206],"detailed":[208],"ones":[209],"A.":[212],"Despite":[213],"differences,":[216],"both":[217,251],"exhibit":[219],"similar":[220],"stereotypical":[221],"their":[224,247],"coverage,":[225],"such":[226],"consistently":[228],"emphasizing":[229],"nationality":[230],"group":[232],"distinctions":[233],"ways":[235],"can":[237],"reinforce":[238],"stereotypes.":[240],"This":[241],"shared":[242],"tendency":[243],"suggests":[244],"that,":[245],"although":[246],"narrative":[248],"strategies":[249],"differ,":[250],"could":[253],"contribute":[254],"broader":[257],"pattern":[258],"stereotype":[260],"reinforcement.":[261]},"counts_by_year":[{"year":2026,"cited_by_count":1}],"updated_date":"2026-04-09T08:11:56.329763","created_date":"2025-10-10T00:00:00"}