{"id":"https://openalex.org/W4409973735","doi":"https://doi.org/10.1145/3698204.3716477","title":"A Tool for Researching how AI Affects Information Seeking","display_name":"A Tool for Researching how AI Affects Information Seeking","publication_year":2025,"publication_date":"2025-03-24","ids":{"openalex":"https://openalex.org/W4409973735","doi":"https://doi.org/10.1145/3698204.3716477"},"language":"en","primary_location":{"id":"doi:10.1145/3698204.3716477","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3698204.3716477","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3698204.3716477","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 ACM SIGIR Conference on Human Information Interaction and Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3698204.3716477","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5002482997","display_name":"Alamir Novin","orcid":"https://orcid.org/0000-0002-8240-0360"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Alamir Novin","raw_affiliation_strings":["University of South Carolina, Columbia, South Carolina, USA"],"raw_orcid":"https://orcid.org/0000-0002-8240-0360","affiliations":[{"raw_affiliation_string":"University of South Carolina, Columbia, South Carolina, USA","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5114280187","display_name":"Georgia Towne","orcid":null},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Georgia Towne","raw_affiliation_strings":["University of South Carolina, Columbia, South Carolina, USA"],"raw_orcid":"https://orcid.org/0009-0005-0413-8773","affiliations":[{"raw_affiliation_string":"University of South Carolina, Columbia, South Carolina, USA","institution_ids":["https://openalex.org/I155781252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I155781252"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11188048,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"396","last_page":"404"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10286","display_name":"Information Retrieval and Search Behavior","score":0.9927999973297119,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T12607","display_name":"Personal Information Management and User Behavior","score":0.989300012588501,"subfield":{"id":"https://openalex.org/subfields/1802","display_name":"Information Systems and Management"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9807000160217285,"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/computer-science","display_name":"Computer science","score":0.5855798125267029},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.3910831809043884},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.3807666003704071}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5855798125267029},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3910831809043884},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.3807666003704071}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3698204.3716477","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3698204.3716477","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3698204.3716477","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 ACM SIGIR Conference on Human Information Interaction and Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3698204.3716477","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3698204.3716477","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3698204.3716477","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2025 ACM SIGIR Conference on Human Information Interaction and Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4409973735.pdf","grobid_xml":"https://content.openalex.org/works/W4409973735.grobid-xml"},"referenced_works_count":29,"referenced_works":["https://openalex.org/W170608365","https://openalex.org/W258964963","https://openalex.org/W1506360956","https://openalex.org/W1969340322","https://openalex.org/W1974816463","https://openalex.org/W2010210047","https://openalex.org/W2019290356","https://openalex.org/W2041333115","https://openalex.org/W2093162167","https://openalex.org/W2172197065","https://openalex.org/W2251463261","https://openalex.org/W2399992943","https://openalex.org/W2504079257","https://openalex.org/W2528669863","https://openalex.org/W2539177311","https://openalex.org/W2594739882","https://openalex.org/W2594745009","https://openalex.org/W2789365936","https://openalex.org/W2913255424","https://openalex.org/W2967979449","https://openalex.org/W3011423189","https://openalex.org/W3152574220","https://openalex.org/W3152665210","https://openalex.org/W4205771332","https://openalex.org/W4243216998","https://openalex.org/W4247890353","https://openalex.org/W4255928670","https://openalex.org/W4401271874","https://openalex.org/W6877337176"],"related_works":["https://openalex.org/W4391375266","https://openalex.org/W2899084033","https://openalex.org/W2748952813","https://openalex.org/W2390279801","https://openalex.org/W4391913857","https://openalex.org/W2358668433","https://openalex.org/W4396701345","https://openalex.org/W2376932109","https://openalex.org/W2001405890","https://openalex.org/W4396696052"],"abstract_inverted_index":{"Information":[0,210],"Scholars":[1,211],"are":[2,74,87],"calling":[3],"for":[4,16,97,158,229],"more":[5],"standardization":[6],"of":[7,29,66,95,114,186,205],"the":[8,11,26,64,125,206,221,227],"metrics":[9],"quantifying":[10],"information-seeking":[12],"processes":[13],"(ISP).Standardizing":[14],"measures":[15],"online":[17],"searching":[18],"is":[19],"challenging":[20],"due":[21],"to":[22,33,42,58,118,140,224],"search":[23,35,60,147,169],"pages":[24,148],"including":[25],"dynamic":[27],"nature":[28],"generative":[30],"AI":[31,170],"adjacent":[32,57],"personalized":[34,59],"results.AI-chatbots":[36],"occasionally":[37,51],"use":[38,92],"queries":[39,73],"as":[40,76],"prompts":[41,77],"generate":[43],"text":[44],"using":[45,226],"large-language":[46],"models":[47],"(LLM).Search":[48],"engines":[49],"also":[50],"include":[52],"Retrieval-Augmented":[53],"Generation":[54],"(RAG)":[55],"results":[56,81,121,197],"results.This":[61],"interface":[62],"hinders":[63],"level":[65],"control":[67],"in":[68,190,220],"experiments":[69,145],"when":[70,90],"two":[71],"similar":[72],"treated":[75],"towards":[78],"very":[79],"different":[80,93,112,119],"and":[82,103,108,110,151,163,171,183,193],"text-generations.In":[83],"addition,":[84],"experiment":[85],"findings":[86],"less":[88],"comparable":[89],"researchers":[91],"combinations":[94,113],"software":[96,228],"data":[98,179],"log":[99,178],"collections":[100],"(e.g.,":[101,106,202],"click-throughs":[102],"time-on-site),":[104],"analysis":[105],"NVivo":[107],"Qualtrics),":[109],"visualizations.These":[111],"platforms":[115],"can":[116],"lead":[117],"statistical":[120],"or":[122],"even":[123],"obnubilate":[124],"research":[126],"metrics.To":[127],"address":[128],"these":[129],"discrepancies,":[130],"this":[131],"study":[132],"introduces":[133],"a":[134],"method":[135,223],"with":[136,142,149,196,215],"three":[137],"key":[138],"automations":[139],"assist":[141],"standardizing":[143],"ISP":[144],"on":[146],"LLMs":[150],"RAG:":[152],"1)":[153],"Controls:":[154],"A":[155],"system":[156],"designed":[157],"Randomized":[159],"Control":[160],"Trial":[161],"Experiments":[162],"A/B":[164],"Tests":[165],"by":[166],"simulating":[167],"Google's":[168],"algorithms;":[172],"2)":[173],"Data":[174],"Collection:":[175],"Automatic":[176],"participant":[177],"collection;":[180],"3)":[181],"Analysis":[182],"Visualization:":[184],"Presentation":[185],"statistically":[187],"significant":[188],"differences":[189],"both":[191],"quantitative":[192],"qualitative":[194],"data,":[195],"visualized":[198],"alongside":[199],"proper":[200],"formatting":[201],"APA":[203],"citations":[204],"p-value).Preliminary":[207],"feedback":[208],"from":[209],"has":[212],"been":[213],"promising,":[214],"86%":[216],"expressing":[217],"sufficient":[218],"value":[219],"proposed":[222],"consider":[225],"their":[230],"future":[231],"projects.":[232]},"counts_by_year":[],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}
