{"id":"https://openalex.org/W4385573372","doi":"https://doi.org/10.18653/v1/2022.findings-emnlp.123","title":"Language as a fingerprint: Self-supervised learning of user encodings using transformers","display_name":"Language as a fingerprint: Self-supervised learning of user encodings using transformers","publication_year":2022,"publication_date":"2022-01-01","ids":{"openalex":"https://openalex.org/W4385573372","doi":"https://doi.org/10.18653/v1/2022.findings-emnlp.123"},"language":"en","primary_location":{"id":"doi:10.18653/v1/2022.findings-emnlp.123","doi":"https://doi.org/10.18653/v1/2022.findings-emnlp.123","is_oa":true,"landing_page_url":"http://dx.doi.org/10.18653/v1/2022.findings-emnlp.123","pdf_url":"https://aclanthology.org/2022.findings-emnlp.123.pdf","source":{"id":"https://openalex.org/S7407096085","display_name":"Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EMNLP 2022","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://aclanthology.org/2022.findings-emnlp.123.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Roberta Rocca","orcid":null,"observed_orcids":[]},"institutions":[{"id":"https://openalex.org/I204337017","display_name":"Aarhus University","ror":"https://ror.org/01aj84f44","country_code":"DK","type":"education","lineage":["https://openalex.org/I204337017"]},{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["DK","US"],"is_corresponding":false,"raw_author_name":"Roberta Rocca","raw_affiliation_strings":["Aarhus University University of Texas at Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Aarhus University University of Texas at Austin","institution_ids":["https://openalex.org/I204337017","https://openalex.org/I86519309"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5089396175","display_name":"Tal Yarkoni","orcid":"https://orcid.org/0000-0002-6558-5113","observed_orcids":["https://orcid.org/0000-0002-6558-5113"]},"institutions":[{"id":"https://openalex.org/I86519309","display_name":"The University of Texas at Austin","ror":"https://ror.org/00hj54h04","country_code":"US","type":"education","lineage":["https://openalex.org/I86519309"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Tal Yarkoni","raw_affiliation_strings":["University of Texas at Austin"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Texas at Austin","institution_ids":["https://openalex.org/I86519309"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4147,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.62435062,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1701","last_page":"1714"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12380","display_name":"Authorship Attribution and Profiling","score":0.9491999745368958,"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":0.9491999745368958,"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/T12488","display_name":"Mental Health via Writing","score":0.04230000078678131,"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"}},{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.004600000102072954,"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/self-supervised-learning","display_name":"self-supervised learning","score":0.7770000100135803},{"id":"https://openalex.org/keywords/triplet-loss","display_name":"triplet loss","score":0.7009999752044678},{"id":"https://openalex.org/keywords/distilbert","display_name":"DistilBERT","score":0.7200000286102295},{"id":"https://openalex.org/keywords/individual-differences","display_name":"individual differences","score":0.6060000061988831},{"id":"https://openalex.org/keywords/author-profiling","display_name":"author profiling","score":0.5289999842643738}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.716434121131897},{"id":"https://openalex.org/C2777826928","wikidata":"https://www.wikidata.org/wiki/Q3745713","display_name":"Fingerprint (computing)","level":2,"score":0.691918134689331},{"id":"https://openalex.org/C66322947","wikidata":"https://www.wikidata.org/wiki/Q11658","display_name":"Transformer","level":3,"score":0.6151106357574463},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4942612648010254},{"id":"https://openalex.org/C168406668","wikidata":"https://www.wikidata.org/wiki/Q178022","display_name":"Fingerprint recognition","level":3,"score":0.4746159613132477},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.36589115858078003},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.32939279079437256},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.18293115496635437},{"id":"https://openalex.org/C119599485","wikidata":"https://www.wikidata.org/wiki/Q43035","display_name":"Electrical engineering","level":1,"score":0.0971621572971344},{"id":"https://openalex.org/C165801399","wikidata":"https://www.wikidata.org/wiki/Q25428","display_name":"Voltage","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/2022.findings-emnlp.123","doi":"https://doi.org/10.18653/v1/2022.findings-emnlp.123","is_oa":true,"landing_page_url":"http://dx.doi.org/10.18653/v1/2022.findings-emnlp.123","pdf_url":"https://aclanthology.org/2022.findings-emnlp.123.pdf","source":{"id":"https://openalex.org/S7407096085","display_name":"Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EMNLP 2022","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/2022.findings-emnlp.123","doi":"https://doi.org/10.18653/v1/2022.findings-emnlp.123","is_oa":true,"landing_page_url":"http://dx.doi.org/10.18653/v1/2022.findings-emnlp.123","pdf_url":"https://aclanthology.org/2022.findings-emnlp.123.pdf","source":{"id":"https://openalex.org/S7407096085","display_name":"Findings of the Association for Computational Linguistics: EMNLP (Findings of EMNLP)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"conference"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Findings of the Association for Computational Linguistics: EMNLP 2022","raw_type":"proceedings-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4385573372.pdf","grobid_xml":"https://content.openalex.org/works/W4385573372.grobid-xml"},"referenced_works_count":59,"referenced_works":["https://openalex.org/W326142932","https://openalex.org/W1596668010","https://openalex.org/W1973871257","https://openalex.org/W2096733369","https://openalex.org/W2119595472","https://openalex.org/W2139229497","https://openalex.org/W2144487656","https://openalex.org/W2153266959","https://openalex.org/W2154887492","https://openalex.org/W2159326821","https://openalex.org/W2252128283","https://openalex.org/W2252241921","https://openalex.org/W2263859238","https://openalex.org/W2511234952","https://openalex.org/W2739672440","https://openalex.org/W2739978983","https://openalex.org/W2759869292","https://openalex.org/W2790228540","https://openalex.org/W2804377263","https://openalex.org/W2806221456","https://openalex.org/W2897042519","https://openalex.org/W2897583329","https://openalex.org/W2937954624","https://openalex.org/W2946202814","https://openalex.org/W2947838315","https://openalex.org/W2953958347","https://openalex.org/W2963530187","https://openalex.org/W2964121744","https://openalex.org/W2964239055","https://openalex.org/W2969401291","https://openalex.org/W2978017171","https://openalex.org/W2980282514","https://openalex.org/W3005717492","https://openalex.org/W3014084332","https://openalex.org/W3035377849","https://openalex.org/W3035509916","https://openalex.org/W3036527026","https://openalex.org/W3040389457","https://openalex.org/W3045555759","https://openalex.org/W3046858091","https://openalex.org/W3100791307","https://openalex.org/W3105797034","https://openalex.org/W3111058005","https://openalex.org/W3133425135","https://openalex.org/W3133702157","https://openalex.org/W3133849783","https://openalex.org/W3134141507","https://openalex.org/W3143569708","https://openalex.org/W3155742828","https://openalex.org/W3156636935","https://openalex.org/W3160467094","https://openalex.org/W3165022283","https://openalex.org/W3172917028","https://openalex.org/W3177080462","https://openalex.org/W3211949871","https://openalex.org/W4223610593","https://openalex.org/W4225535697","https://openalex.org/W4285141183","https://openalex.org/W4289222848"],"related_works":["https://openalex.org/W3130666114","https://openalex.org/W7134059793","https://openalex.org/W4392702318","https://openalex.org/W4396217674","https://openalex.org/W6964382308","https://openalex.org/W7163679655","https://openalex.org/W3105797034","https://openalex.org/W6885051298","https://openalex.org/W2945578088","https://openalex.org/W3208383346"],"abstract_inverted_index":{"The":[0],"way":[1],"we":[2,8,17,80,98,138],"talk":[3],"carries":[4],"information":[5,126],"about":[6,19,127],"who":[7],"are.Demographics,":[9],"personality,":[10],"clinical":[11],"conditions,":[12],"political":[13],"preferences":[14],"influence":[15],"what":[16],"speak":[18],"and":[20,57,118,135,164,166],"how,":[21],"suggesting":[22],"that":[23,106,119,141],"many":[24,50],"individual":[25,55],"attributes":[26,41,66,76],"could":[27],"be":[28],"inferred":[29],"from":[30,67],"adequate":[31],"encodings":[32,89],"of":[33,95,116,132],"linguistic":[34,114],"behavior.Conversely,":[35],"conditioning":[36,71],"text":[37,72],"representations":[38,59,73],"on":[39,54,63,70,74,101,112],"author":[40],"has":[42,60],"been":[43],"shown":[44],"to":[45,85,123,146],"improve":[46],"model":[47],"performance":[48,153],"in":[49,161],"NLP":[51],"tasks.Previous":[52],"research":[53],"differences":[56],"language":[58],"mainly":[61],"focused":[62],"predicting":[64],"selected":[65],"text,":[68],"or":[69],"such":[75],"for":[77,155],"author-based":[78],"contextualization.Here,":[79],"present":[81],"a":[82,92,130],"self-supervised":[83],"approach":[84],"learning":[86],"language-based":[87,162],"user":[88,149],"using":[90],"transformers.Using":[91],"large":[93],"corpus":[94],"Reddit":[96],"submissions,":[97],"fine-tune":[99],"DistilBERT":[100],"user-based":[102,156],"triplet":[103],"loss.We":[104],"show":[105],"fine-tuned":[107],"models":[108],"can":[109],"pick":[110],"up":[111],"complex":[113],"signatures":[115],"users,":[117],"they":[120],"are":[121],"able":[122],"infer":[124],"rich":[125],"their":[128],"profiles.Through":[129],"series":[131],"intrinsic":[133],"analyses":[134],"probing":[136],"tasks,":[137],"provide":[139],"evidence":[140],"fine-tuning":[142],"enhances":[143],"models'":[144],"ability":[145],"abstract":[147],"generalizable":[148],"information,":[150],"which":[151],"yields":[152],"advantages":[154],"downstream":[157],"tasks.We":[158],"discuss":[159],"applications":[160],"assessment":[163],"contextualized":[165],"personalized":[167],"NLP.":[168]},"counts_by_year":[{"year":2026,"cited_by_count":1},{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":2}],"updated_date":"2026-10-26T11:51:55.731654","created_date":"2023-08-05T00:00:00"}