{"id":"https://openalex.org/W7165399564","doi":"https://doi.org/10.48550/arxiv.2606.20064","title":"AI Conversational Interviewing: Scaling Up Semi-Structured and In-depth Interviews","display_name":"AI Conversational Interviewing: Scaling Up Semi-Structured and In-depth Interviews","publication_year":2026,"publication_date":"2026-06-18","ids":{"openalex":"https://openalex.org/W7165399564","doi":"https://doi.org/10.48550/arxiv.2606.20064"},"language":null,"primary_location":{"id":"doi:10.48550/arxiv.2606.20064","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20064","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"type":"preprint","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.48550/arxiv.2606.20064","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5004036470","display_name":"Alexander Wuttke","orcid":"https://orcid.org/0000-0002-9579-5357"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Wuttke, Alexander","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5129583919","display_name":"Max Melchior Lang","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Lang, Max Melchior","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5003936190","display_name":"Christopher Klamm","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Klamm, Christopher","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5114439649","display_name":"Quirin W\u00fcrschinger","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"W\u00fcrschinger, Quirin","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5138994354","display_name":"Frauke Kreuter","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kreuter, Frauke","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":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/T11539","display_name":"Survey Methodology and Nonresponse","score":0.4318000078201294,"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"}},"topics":[{"id":"https://openalex.org/T11539","display_name":"Survey Methodology and Nonresponse","score":0.4318000078201294,"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/T12679","display_name":"Focus Groups and Qualitative Methods","score":0.11919999867677689,"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":0.0502999983727932,"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/interview","display_name":"Interview","score":0.782800018787384},{"id":"https://openalex.org/keywords/diversity","display_name":"Diversity (politics)","score":0.5491999983787537},{"id":"https://openalex.org/keywords/public-opinion","display_name":"Public opinion","score":0.45210000872612},{"id":"https://openalex.org/keywords/pipeline","display_name":"Pipeline (software)","score":0.4122999906539917},{"id":"https://openalex.org/keywords/data-collection","display_name":"Data collection","score":0.34869998693466187},{"id":"https://openalex.org/keywords/public-speaking","display_name":"Public speaking","score":0.3246000111103058}],"concepts":[{"id":"https://openalex.org/C24845683","wikidata":"https://www.wikidata.org/wiki/Q178651","display_name":"Interview","level":2,"score":0.782800018787384},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.6187000274658203},{"id":"https://openalex.org/C2781316041","wikidata":"https://www.wikidata.org/wiki/Q1230584","display_name":"Diversity (politics)","level":2,"score":0.5491999983787537},{"id":"https://openalex.org/C134698397","wikidata":"https://www.wikidata.org/wiki/Q17946","display_name":"Public opinion","level":3,"score":0.45210000872612},{"id":"https://openalex.org/C75630572","wikidata":"https://www.wikidata.org/wiki/Q538904","display_name":"Applied psychology","level":1,"score":0.45089998841285706},{"id":"https://openalex.org/C43521106","wikidata":"https://www.wikidata.org/wiki/Q2165493","display_name":"Pipeline (software)","level":2,"score":0.4122999906539917},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.3546999990940094},{"id":"https://openalex.org/C133462117","wikidata":"https://www.wikidata.org/wiki/Q4929239","display_name":"Data collection","level":2,"score":0.34869998693466187},{"id":"https://openalex.org/C509550671","wikidata":"https://www.wikidata.org/wiki/Q126945","display_name":"Medical education","level":1,"score":0.32600000500679016},{"id":"https://openalex.org/C522180918","wikidata":"https://www.wikidata.org/wiki/Q18342738","display_name":"Public speaking","level":2,"score":0.3246000111103058},{"id":"https://openalex.org/C198477413","wikidata":"https://www.wikidata.org/wiki/Q7647069","display_name":"Survey data collection","level":2,"score":0.3158999979496002},{"id":"https://openalex.org/C2992826032","wikidata":"https://www.wikidata.org/wiki/Q17945","display_name":"Public discourse","level":3,"score":0.3127000033855438},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.3102000057697296},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.29840001463890076},{"id":"https://openalex.org/C39549134","wikidata":"https://www.wikidata.org/wiki/Q133080","display_name":"Public relations","level":1,"score":0.2946999967098236},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2809999883174896},{"id":"https://openalex.org/C3020580240","wikidata":"https://www.wikidata.org/wiki/Q663272","display_name":"Expert opinion","level":2,"score":0.28060001134872437},{"id":"https://openalex.org/C80245801","wikidata":"https://www.wikidata.org/wiki/Q1477475","display_name":"Semi-structured interview","level":3,"score":0.26899999380111694},{"id":"https://openalex.org/C139621336","wikidata":"https://www.wikidata.org/wiki/Q3190382","display_name":"Economic Justice","level":2,"score":0.2522999942302704},{"id":"https://openalex.org/C147859227","wikidata":"https://www.wikidata.org/wiki/Q294217","display_name":"Public sector","level":2,"score":0.2502000033855438}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.48550/arxiv.2606.20064","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20064","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"}],"best_oa_location":{"id":"doi:10.48550/arxiv.2606.20064","is_oa":true,"landing_page_url":"https://doi.org/10.48550/arxiv.2606.20064","pdf_url":null,"source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":"2331-8422","issn":["2331-8422"],"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":"Preprint"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.8209848999977112,"display_name":"Reduced inequalities"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"Public":[0],"opinion":[1,68,237],"research":[2],"has":[3,49],"long":[4],"faced":[5],"a":[6,62,117,124,146,163,224],"trade-off":[7],"between":[8],"depth":[9],"and":[10,102,111,136,148,160,216],"scale:":[11],"standardized":[12,125,165,202],"surveys":[13],"enable":[14],"large-scale":[15],"measurement":[16],"but":[17,42],"restrict":[18],"respondents":[19,132,185],"to":[20,53,75,92,103,151,223,231],"researcher-defined":[21],"categories,":[22],"obscuring":[23],"the":[24,77,87,94,152,188,192,201,220,233],"diversity":[25],"of":[26,80,89,176,191,200,235],"unexpected":[27],"considerations":[28,159],"that":[29,162],"underlie":[30],"public":[31,67,236],"sentiment.":[32],"More":[33],"conversational":[34,81,156],"interviews":[35],"provide":[36],"richer":[37],"insights":[38],"through":[39,98],"open-ended":[40,66],"probing,":[41],"their":[43],"reliance":[44],"on":[45,127,227],"trained":[46],"human":[47],"interviewers":[48],"kept":[50],"them":[51],"difficult":[52],"scale.":[54],"This":[55],"study":[56,118,221],"introduces":[57],"AI":[58,142,193],"Conversational":[59,143],"Interviewing":[60,144],"as":[61,145,171],"method":[63],"for":[64,84],"collecting":[65],"data":[69,83,215],"at":[70,196],"scale,":[71],"pursuing":[72],"three":[73],"objectives:":[74],"demonstrate":[76],"analytical":[78],"value":[79],"text":[82],"questions":[85],"beyond":[86],"reach":[88],"closed-ended":[90],"items;":[91],"assess":[93],"method's":[95],"practical":[96],"viability":[97],"participants'":[99],"own":[100],"evaluations;":[101],"inform":[104],"implementation":[105],"by":[106,210],"experimentally":[107],"comparing":[108],"voice-based,":[109],"chat-based,":[110],"free-choice":[112],"interview":[113,122,194],"modes.":[114],"We":[115],"conducted":[116],"combining":[119],"an":[120],"AI-led":[121],"with":[123,180],"survey":[126,203],"migration":[128,177],"policy":[129],"among":[130,178],"571":[131],"recruited":[133],"via":[134],"Prolific":[135],"Payback":[137],"Panel.":[138],"The":[139,155],"findings":[140],"establish":[141],"viable":[147],"valuable":[149],"addition":[150],"social-science":[153],"toolkit.":[154],"transcripts":[157],"surface":[158],"reasoning":[161],"comprehensive":[164],"battery":[166],"does":[167],"not":[168],"capture":[169],"such":[170],"markedly":[172],"different":[173],"mental":[174],"models":[175],"subgroups":[179],"similar":[181],"attitudes":[182],"levels.":[183],"Among":[184],"who":[186],"completed":[187],"interview,":[189],"evaluations":[190],"were":[195],"or":[197],"above":[198],"those":[199],"across":[204],"modes,":[205],"although":[206],"completion":[207],"itself":[208],"varied":[209],"condition.":[211],"By":[212],"releasing":[213],"open":[214],"open-source":[217],"pipeline":[218],"materials,":[219],"contributes":[222],"growing":[225],"literature":[226],"harnessing":[228],"artificial":[229],"intelligence":[230],"expand":[232],"methods":[234],"measurement.":[238]},"counts_by_year":[],"updated_date":"2026-07-28T07:46:37.118299","created_date":"2026-06-20T00:00:00"}
