{"id":"https://openalex.org/W7125526992","doi":"https://doi.org/10.1109/ichi64645.2025.00049\">https://doi.org/10.1109/ichi64645.2025.00049</a></p","title":"Automated Reddit Data Annotation with Large Language Models","display_name":"Automated Reddit Data Annotation with Large Language Models","publication_year":2025,"publication_date":"2025-01-01","ids":{"openalex":"https://openalex.org/W7125526992","doi":"https://doi.org/10.1109/ichi64645.2025.00049\">https://doi.org/10.1109/ichi64645.2025.00049</a></p"},"language":"en","primary_location":{"id":"pmh:oai:scholarcommons.sc.edu:acorn_pub-1859","doi":"https://doi.org/10.1109/ichi64645.2025.00049\">https://doi.org/10.1109/ichi64645.2025.00049</a></p","is_oa":false,"landing_page_url":"https://scholarcommons.sc.edu/acorn_pub/858","pdf_url":null,"source":{"id":"https://openalex.org/S4306401386","display_name":"Scholar Commons (University of South Carolina)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I155781252","host_organization_name":"University of South Carolina","host_organization_lineage":["https://openalex.org/I155781252"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Publications","raw_type":"text"},"volume":null,"type":"article","is_traditional":true,"indexed_in":[],"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/A5092489810","display_name":"Sai Krishna Revanth Vuruma","orcid":"https://orcid.org/0009-0009-3741-9343","observed_orcids":["https://orcid.org/0009-0009-3741-9343"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Vuruma, Sai","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5084106852","display_name":"Dezhi Wu","orcid":"https://orcid.org/0000-0002-7900-0542","observed_orcids":["https://orcid.org/0000-0002-7900-0542"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wu, Dezhi","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101347596","display_name":"Saborny Sen Gupta","orcid":"https://orcid.org/0009-0008-0937-5366","observed_orcids":["https://orcid.org/0009-0008-0937-5366"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Gupta, Saborny Sen","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5097358282","display_name":"Lucas Aust","orcid":"https://orcid.org/0009-0009-7363-3072","observed_orcids":["https://orcid.org/0009-0009-7363-3072"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Aust, Lucas","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005306539","display_name":"Valerie Lookingbill","orcid":"https://orcid.org/0000-0003-1453-2633","observed_orcids":["https://orcid.org/0000-0003-1453-2633"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lookingbill, Valerie","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5099881251","display_name":"Wyatt Bellamy","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Bellamy, Wyatt","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5087938537","display_name":"Yang Ren","orcid":"https://orcid.org/0000-0002-6128-5826","observed_orcids":["https://orcid.org/0000-0002-6128-5826","https://orcid.org/0000-0003-2663-6878"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ren, Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003327929","display_name":"Erin M. Kasson","orcid":"https://orcid.org/0000-0003-4888-3319","observed_orcids":["https://orcid.org/0000-0003-4888-3319","https://orcid.org/0009-0008-7120-5050"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kasson, Erin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123633514","display_name":"Li Shiun Chen","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Chen, Li Shiun","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5104564276","display_name":"Patricia Cavazos-Rehg","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Cavazos-Rehg, Patricia","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5090825893","display_name":"Dian Hu","orcid":"https://orcid.org/0000-0003-1277-142X","observed_orcids":["https://orcid.org/0000-0003-1277-142X"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Hu, Dian","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5123701666","display_name":"Hongfang Liu","orcid":null,"observed_orcids":[]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Liu, Hongfang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5010869663","display_name":"Ming S. Huang","orcid":"https://orcid.org/0000-0001-7367-3626","observed_orcids":["https://orcid.org/0000-0001-7367-3626"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Huang, Ming","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.0,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"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":0.6884999871253967,"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":0.6884999871253967,"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/T10060","display_name":"Smoking Behavior and Cessation","score":0.18569999933242798,"subfield":{"id":"https://openalex.org/subfields/2739","display_name":"Public Health, Environmental and Occupational Health"},"field":{"id":"https://openalex.org/fields/27","display_name":"Medicine"},"domain":{"id":"https://openalex.org/domains/4","display_name":"Health Sciences"}},{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.05959999933838844,"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/reddit","display_name":"Reddit","score":0.6959999799728394},{"id":"https://openalex.org/keywords/large-language-models","display_name":"large language models","score":0.8479999899864197},{"id":"https://openalex.org/keywords/automatic-annotation","display_name":"automatic annotation","score":0.5770000219345093},{"id":"https://openalex.org/keywords/prompting-strategies","display_name":"prompting strategies","score":0.8029999732971191},{"id":"https://openalex.org/keywords/chain-of-thought-prompting","display_name":"chain-of-thought prompting","score":0.9309999942779541},{"id":"https://openalex.org/keywords/few-shot-prompting","display_name":"few-shot prompting","score":0.7390000224113464},{"id":"https://openalex.org/keywords/vaping-cessation","display_name":"vaping cessation","score":0.4779999852180481},{"id":"https://openalex.org/keywords/generative-ai","display_name":"generative AI","score":0.777999997138977}],"concepts":[{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.7185999751091003},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6570000052452087},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.6521999835968018},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5396000146865845},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5138999819755554},{"id":"https://openalex.org/C2778689934","wikidata":"https://www.wikidata.org/wiki/Q1313396","display_name":"Headline","level":2,"score":0.4830999970436096},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.43639999628067017},{"id":"https://openalex.org/C2776321320","wikidata":"https://www.wikidata.org/wiki/Q857525","display_name":"Annotation","level":2,"score":0.4056999981403351},{"id":"https://openalex.org/C167966045","wikidata":"https://www.wikidata.org/wiki/Q5532625","display_name":"Generative model","level":3,"score":0.4000999927520752},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.39259999990463257},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.38989999890327454},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.3856000006198883},{"id":"https://openalex.org/C512170562","wikidata":"https://www.wikidata.org/wiki/Q173799","display_name":"Entertainment","level":2,"score":0.365200012922287},{"id":"https://openalex.org/C2776145971","wikidata":"https://www.wikidata.org/wiki/Q30673951","display_name":"Labeled data","level":2,"score":0.3345000147819519},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.31690001487731934},{"id":"https://openalex.org/C171686336","wikidata":"https://www.wikidata.org/wiki/Q3532085","display_name":"Topic model","level":2,"score":0.3098999857902527},{"id":"https://openalex.org/C148524875","wikidata":"https://www.wikidata.org/wiki/Q6975395","display_name":"F1 score","level":2,"score":0.3075999915599823},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.3066999912261963},{"id":"https://openalex.org/C138816342","wikidata":"https://www.wikidata.org/wiki/Q189603","display_name":"Public health","level":2,"score":0.30070000886917114},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.2987000048160553},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.29820001125335693},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.2831999957561493},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.27410000562667847},{"id":"https://openalex.org/C108827166","wikidata":"https://www.wikidata.org/wiki/Q175975","display_name":"Internet privacy","level":1,"score":0.2734000086784363},{"id":"https://openalex.org/C39890363","wikidata":"https://www.wikidata.org/wiki/Q36108","display_name":"Generative grammar","level":2,"score":0.27149999141693115},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.2712000012397766},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.26910001039505005}],"mesh":[],"locations_count":1,"locations":[{"id":"pmh:oai:scholarcommons.sc.edu:acorn_pub-1859","doi":"https://doi.org/10.1109/ichi64645.2025.00049\">https://doi.org/10.1109/ichi64645.2025.00049</a></p","is_oa":false,"landing_page_url":"https://scholarcommons.sc.edu/acorn_pub/858","pdf_url":null,"source":{"id":"https://openalex.org/S4306401386","display_name":"Scholar Commons (University of South Carolina)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I155781252","host_organization_name":"University of South Carolina","host_organization_lineage":["https://openalex.org/I155781252"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Publications","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.8199999928474426}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W4396818530","https://openalex.org/W4400267137","https://openalex.org/W7118012977","https://openalex.org/W4280529280","https://openalex.org/W4311374371","https://openalex.org/W4211235060","https://openalex.org/W7220331310","https://openalex.org/W3196381353","https://openalex.org/W4390992314","https://openalex.org/W4390849897"],"abstract_inverted_index":{"In":[0,105],"recent":[1],"years,":[2],"the":[3,12,41,47,61,85,174,209,212,216,228],"United":[4],"States":[5],"has":[6],"witnessed":[7],"a":[8,21,81,110,198],"significant":[9,82],"surge":[10],"in":[11,24,44,148,235,241],"popularity":[13],"of":[14,26,63,84,176,218,230],"vaping":[15,29,51,115,168],"or":[16],"e-cigarette":[17,27],"use,":[18],"leading":[19],"to":[20,49,60,88,119,150,207,211],"notable":[22],"rise":[23],"cases":[25],"and":[28,38,53,78,141,154,163,181,194,197,214],"use":[30,72],"associated":[31],"lung":[32],"injury":[33],"(EVALI)":[34],"that":[35,246],"caused":[36],"hospitalizations":[37],"fatalities":[39],"during":[40],"EVALI":[42],"outbreak":[43],"2019,":[45],"highlighting":[46],"urgency":[48],"comprehend":[50],"behaviors":[52],"develop":[54],"effective":[55],"strategies":[56,188,220],"for":[57,74,101,165],"cessation.":[58],"Due":[59],"ubiquity":[62],"social":[64,92,236],"media":[65,93,237],"platforms,":[66],"over":[67],"4.7":[68],"billion":[69],"users":[70],"worldwide":[71],"them":[73],"connectivity,":[75],"communications,":[76],"news,":[77],"entertainment":[79],"with":[80],"portion":[83],"discourse":[86],"related":[87],"health,":[89],"thereby":[90],"establishing":[91],"data":[94,99,238],"as":[95,132,159,190],"an":[96],"invaluable":[97],"organic":[98],"resource":[100],"public":[102],"health":[103],"research.":[104],"this":[106],"study,":[107],"we":[108,203],"extracted":[109],"sample":[111],"dataset":[112],"from":[113],"one":[114],"sub-community":[116],"on":[117],"Reddit":[118],"analyze":[120],"users'":[121,243],"quit-vaping":[122],"intentions.":[123],"We":[124],"leveraged":[125],"latest":[126],"Large":[127],"Language":[128],"Models":[129],"(LLMs)":[130],"such":[131,158,189],"OpenAI's":[133],"GPT-4,":[134],"Meta's":[135],"LLAMA":[136],"3.1,":[137],"Microsoft's":[138],"Phi":[139],"3.5":[140],"Google's":[142],"Gemini":[143],"1.5":[144],"&":[145],"Gemma":[146],"2,":[147],"addition":[149],"traditional":[151],"machine":[152],"learning":[153,156],"deep":[155],"models":[157,178],"BERT,":[160],"CNN,":[161],"SVM":[162],"XGBoost":[164],"sentence-level":[166],"quit":[167],"intention":[169],"detection.":[170,250],"This":[171],"study":[172],"compares":[173],"outcomes":[175],"these":[177,219],"against":[179,221],"layman":[180],"clinical":[182],"expert":[183],"annotations.":[184],"Using":[185],"different":[186],"prompting":[187],"zero-shot,":[191],"one-shot,":[192],"few-shot":[193],"chain-of-thought":[195],"prompting,":[196],"custom":[199],"variable":[200],"called":[201],"'detail,'":[202],"developed":[204],"8":[205],"prompts":[206],"explain":[208],"task":[210],"LLMs":[213],"evaluated":[215],"performance":[217],"each":[222],"other.":[223],"Our":[224],"preliminary":[225],"findings":[226],"emphasize":[227],"potential":[229],"using":[231],"Generative":[232],"AI":[233],"tools":[234],"analysis,":[239],"especially":[240],"identifying":[242],"subtle":[244],"intentions":[245],"may":[247],"elude":[248],"human":[249]},"counts_by_year":[],"updated_date":"2026-11-07T11:25:07.637180","created_date":"2026-01-24T00:00:00"}
