{"id":"https://openalex.org/W4416718514","doi":"https://doi.org/10.1007/s44163-025-00635-9","title":"Interpretable stance detection in social media via topic-guided transformers","display_name":"Interpretable stance detection in social media via topic-guided transformers","publication_year":2025,"publication_date":"2025-11-26","ids":{"openalex":"https://openalex.org/W4416718514","doi":"https://doi.org/10.1007/s44163-025-00635-9"},"language":"en","primary_location":{"id":"doi:10.1007/s44163-025-00635-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00635-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00635-9.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00635-9.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5106618531","display_name":"Rathinasamy Muthusami","orcid":"https://orcid.org/0000-0001-7322-8653"},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Rathinasamy Muthusami","raw_affiliation_strings":["Department of Computer Applications, Dr. Mahalingam College of Engineering and Technology, Pollachi, Tamil Nadu, India"],"affiliations":[{"raw_affiliation_string":"Department of Computer Applications, Dr. Mahalingam College of Engineering and Technology, Pollachi, Tamil Nadu, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103760948","display_name":"Kandhasamy Saritha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kandhasamy Saritha","raw_affiliation_strings":["Department of Mathematics, P. A. College of Engineering and Technology, Pollachi, Tamil Nadu, India"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, P. A. College of Engineering and Technology, Pollachi, Tamil Nadu, India","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084912596","display_name":"K. Srinivasa Rao","orcid":null},"institutions":[{"id":"https://openalex.org/I885392262","display_name":"GITAM University","ror":"https://ror.org/0440p1d37","country_code":"IN","type":"education","lineage":["https://openalex.org/I885392262"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Kolli Srinivasa Rao","raw_affiliation_strings":["Department of Operations & Supply Chain, Gitam School of Business, GITAM (Deemed to Be University), Visakhapatnam, Andhra Pradesh, India"],"affiliations":[{"raw_affiliation_string":"Department of Operations & Supply Chain, Gitam School of Business, GITAM (Deemed to Be University), Visakhapatnam, Andhra Pradesh, India","institution_ids":["https://openalex.org/I885392262"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099169327","display_name":"Palanisamy Sugapriya","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Palanisamy Sugapriya","raw_affiliation_strings":["Department of Mathematics, K. Ramakrishnan College of Engineering, Tiruchirappalli, Tamil Nadu, India"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, K. Ramakrishnan College of Engineering, Tiruchirappalli, Tamil Nadu, India","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5032522283","display_name":"G. Saveetha","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"G. Saveetha","raw_affiliation_strings":["Department of Mathematics, Kongunadu College of Engineering and Technology, Trichy, Tamil Nadu, India"],"affiliations":[{"raw_affiliation_string":"Department of Mathematics, Kongunadu College of Engineering and Technology, Trichy, Tamil Nadu, India","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5106618531"],"corresponding_institution_ids":[],"apc_list":{"value":990,"currency":"EUR","value_usd":1067},"apc_paid":{"value":990,"currency":"EUR","value_usd":1067},"fwci":5.3419,"has_fulltext":true,"cited_by_count":2,"citation_normalized_percentile":{"value":0.95937878,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":98,"max":99},"biblio":{"volume":"5","issue":"1","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":0.47380000352859497,"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":0.47380000352859497,"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":0.20919999480247498,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.13699999451637268,"subfield":{"id":"https://openalex.org/subfields/3300","display_name":"General Social Sciences"},"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/interpretability","display_name":"Interpretability","score":0.9372000098228455},{"id":"https://openalex.org/keywords/ambiguity","display_name":"Ambiguity","score":0.5785999894142151},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.555899977684021},{"id":"https://openalex.org/keywords/topic-model","display_name":"Topic model","score":0.42340001463890076},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.3808000087738037},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.37400001287460327},{"id":"https://openalex.org/keywords/word-embedding","display_name":"Word embedding","score":0.35420000553131104},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.33250001072883606},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.32429999113082886}],"concepts":[{"id":"https://openalex.org/C2781067378","wikidata":"https://www.wikidata.org/wiki/Q17027399","display_name":"Interpretability","level":2,"score":0.9372000098228455},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7281000018119812},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6227999925613403},{"id":"https://openalex.org/C2780522230","wikidata":"https://www.wikidata.org/wiki/Q1140419","display_name":"Ambiguity","level":2,"score":0.5785999894142151},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.555899977684021},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4819999933242798},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.42340001463890076},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.39899998903274536},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.3808000087738037},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.37400001287460327},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3684000074863434},{"id":"https://openalex.org/C2777462759","wikidata":"https://www.wikidata.org/wiki/Q18395344","display_name":"Word embedding","level":3,"score":0.35420000553131104},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.33250001072883606},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.32429999113082886},{"id":"https://openalex.org/C46686674","wikidata":"https://www.wikidata.org/wiki/Q466303","display_name":"Boosting (machine learning)","level":2,"score":0.31700000166893005},{"id":"https://openalex.org/C2780513914","wikidata":"https://www.wikidata.org/wiki/Q18210350","display_name":"Bottleneck","level":2,"score":0.31540000438690186},{"id":"https://openalex.org/C174348530","wikidata":"https://www.wikidata.org/wiki/Q188635","display_name":"Bridging (networking)","level":2,"score":0.2939999997615814},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.2921999990940094},{"id":"https://openalex.org/C86251818","wikidata":"https://www.wikidata.org/wiki/Q816754","display_name":"Benchmarking","level":2,"score":0.2897999882698059},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.28940001130104065},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.28870001435279846},{"id":"https://openalex.org/C26517878","wikidata":"https://www.wikidata.org/wiki/Q228039","display_name":"Key (lock)","level":2,"score":0.27480000257492065},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.2718000113964081},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.2711000144481659},{"id":"https://openalex.org/C2781181686","wikidata":"https://www.wikidata.org/wiki/Q4226068","display_name":"Coherence (philosophical gambling strategy)","level":2,"score":0.26910001039505005},{"id":"https://openalex.org/C44291984","wikidata":"https://www.wikidata.org/wiki/Q1074173","display_name":"Question answering","level":2,"score":0.26019999384880066},{"id":"https://openalex.org/C2776990098","wikidata":"https://www.wikidata.org/wiki/Q13579947","display_name":"Misinformation","level":2,"score":0.25920000672340393},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.2563999891281128},{"id":"https://openalex.org/C11693617","wikidata":"https://www.wikidata.org/wiki/Q181839","display_name":"Pragmatics","level":2,"score":0.25589999556541443},{"id":"https://openalex.org/C94124525","wikidata":"https://www.wikidata.org/wiki/Q912550","display_name":"Categorization","level":2,"score":0.2531999945640564}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1007/s44163-025-00635-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00635-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00635-9.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:7bf990bd27864be29ef2f44326763c07","is_oa":true,"landing_page_url":"https://doaj.org/article/7bf990bd27864be29ef2f44326763c07","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Discover Artificial Intelligence, Vol 5, Iss 1, Pp 1-26 (2025)","raw_type":"article"}],"best_oa_location":{"id":"doi:10.1007/s44163-025-00635-9","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s44163-025-00635-9","pdf_url":"https://link.springer.com/content/pdf/10.1007/s44163-025-00635-9.pdf","source":{"id":"https://openalex.org/S4210220416","display_name":"Discover Artificial Intelligence","issn_l":"2731-0809","issn":["2731-0809"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310319965","host_organization_name":"Springer Nature","host_organization_lineage":["https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Discover Artificial Intelligence","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4416718514.pdf"},"referenced_works_count":27,"referenced_works":["https://openalex.org/W2096974619","https://openalex.org/W2099813784","https://openalex.org/W2128925311","https://openalex.org/W2174706414","https://openalex.org/W2347127863","https://openalex.org/W2786672974","https://openalex.org/W2896457183","https://openalex.org/W2963065179","https://openalex.org/W2965373594","https://openalex.org/W2970597249","https://openalex.org/W3033317208","https://openalex.org/W3166287017","https://openalex.org/W3173991475","https://openalex.org/W3199505005","https://openalex.org/W4205184193","https://openalex.org/W4226169356","https://openalex.org/W4280590270","https://openalex.org/W4287322452","https://openalex.org/W4287634470","https://openalex.org/W4292779060","https://openalex.org/W4324148013","https://openalex.org/W4324392584","https://openalex.org/W4391839376","https://openalex.org/W4395052272","https://openalex.org/W4400853276","https://openalex.org/W4403786575","https://openalex.org/W4412835254"],"related_works":[],"abstract_inverted_index":{"Stance":[0,118],"detection":[1],"in":[2,9,160,226],"social":[3,11,219],"media":[4],"is":[5],"a":[6,176,231],"critical":[7],"task":[8],"computational":[10],"science,":[12],"supporting":[13],"the":[14,25,116,183],"analysis":[15,181],"of":[16,31,127,185],"ideological":[17],"polarization,":[18],"public":[19],"opinion,":[20],"and":[21,28,60,96,105,115,129,140,175,193,198,202,212,224,239],"sociopolitical":[22],"discourse.":[23],"However,":[24],"brevity,":[26],"noise,":[27],"contextual":[29,98],"ambiguity":[30],"user-generated":[32],"content":[33],"pose":[34],"significant":[35],"challenges":[36],"for":[37,76,83,234],"traditional":[38],"NLP":[39],"models,":[40],"while":[41,179],"large":[42],"language":[43],"models":[44],"(LLMs),":[45],"despite":[46],"their":[47],"impressive":[48],"zero-shot":[49],"capabilities,":[50],"often":[51],"act":[52],"as":[53,135],"opaque":[54],"black":[55],"boxes":[56],"with":[57,81],"limited":[58],"interpretability":[59,168,225],"domain":[61],"adaptability.":[62],"To":[63],"overcome":[64],"these":[65],"limitations,":[66],"we":[67,166,190],"propose":[68],"an":[69],"interpretable":[70],"hybrid":[71],"framework":[72],"that":[73,121],"combines":[74],"BERTopic":[75],"unsupervised":[77],"semantic":[78],"topic":[79],"discovery":[80],"RoBERTa":[82],"sentiment-informed":[84],"stance":[85,210,227],"classification.":[86],"Our":[87],"approach":[88],"explicitly":[89],"fuses":[90],"latent":[91],"topical":[92],"structure,":[93],"sentiment":[94],"polarity,":[95],"deep":[97],"embeddings,":[99],"enabling":[100],"both":[101],"high":[102],"predictive":[103],"accuracy":[104],"transparent":[106],"explanatory":[107],"insights.":[108],"Extensive":[109],"evaluations":[110],"on":[111],"SemEval-2016":[112],"Task":[113],"6":[114],"COVID-19":[117],"Dataset":[119],"demonstrate":[120],"our":[122],"model":[123],"achieves":[124],"macro-F1":[125],"scores":[126],"78.4%":[128],"77.2%,":[130],"surpassing":[131],"competitive":[132],"baselines":[133],"such":[134],"TextCNN,":[136],"BiLSTM-Attention,":[137],"fine-tuned":[138],"BERT,":[139],"CT-BERT.":[141],"Topic":[142,154],"coherence":[143],"metrics":[144],"(NPMI,":[145],"UCI,":[146],"UMass)":[147],"further":[148],"confirm":[149],"BERTopic\u2019s":[150],"superiority":[151],"over":[152],"Structural":[153],"Modeling":[155],"(STM),":[156],"underscoring":[157],"its":[158],"effectiveness":[159],"short-text":[161],"settings.":[162],"Beyond":[163],"quantitative":[164],"results,":[165],"enhance":[167],"through":[169],"topic\u2013stance":[170],"heatmaps,":[171],"qualitative":[172],"case":[173],"studies,":[174],"human-centered":[177],"evaluation,":[178],"ablation":[180],"validates":[182],"contribution":[184],"each":[186],"pipeline":[187],"component.":[188],"Finally,":[189],"discuss":[191],"ethical":[192],"societal":[194],"risks,":[195],"cost":[196],"considerations,":[197],"real-world":[199],"deployment":[200],"implications,":[201],"outline":[203],"future":[204],"directions":[205],"including":[206],"multilingual":[207],"expansion,":[208],"real-time":[209],"monitoring,":[211],"human-in-the-loop":[213],"integration.":[214],"This":[215],"work":[216],"advances":[217],"explainable":[218],"AI":[220],"by":[221],"bridging":[222],"performance":[223],"detection,":[228],"making":[229],"it":[230],"powerful":[232],"tool":[233],"opinion":[235],"mining,":[236],"policy":[237],"analysis,":[238],"misinformation":[240],"tracking.":[241]},"counts_by_year":[{"year":2026,"cited_by_count":2}],"updated_date":"2026-03-17T17:19:04.345684","created_date":"2025-11-27T00:00:00"}
