{"id":"https://openalex.org/W2963675570","doi":"https://doi.org/10.18653/v1/d16-1152","title":"Toward Socially-Infused Information Extraction: Embedding Authors, Mentions, and Entities","display_name":"Toward Socially-Infused Information Extraction: Embedding Authors, Mentions, and Entities","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2963675570","doi":"https://doi.org/10.18653/v1/d16-1152","mag":"2963675570"},"language":"en","primary_location":{"id":"doi:10.18653/v1/d16-1152","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d16-1152","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.18653/v1/d16-1152","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5100657565","display_name":"Yi Yang","orcid":"https://orcid.org/0000-0001-8863-112X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Yi Yang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5076904467","display_name":"Ming\u2010Wei Chang","orcid":"https://orcid.org/0000-0002-0137-8895"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Ming-Wei Chang","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5047699861","display_name":"Jacob Eisenstein","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jacob Eisenstein","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":22,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1452","last_page":"1461"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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/T10028","display_name":"Topic Modeling","score":0.9998999834060669,"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/T10064","display_name":"Complex Network Analysis Techniques","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11273","display_name":"Advanced Graph Neural Networks","score":0.9965999722480774,"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/computer-science","display_name":"Computer science","score":0.7947285175323486},{"id":"https://openalex.org/keywords/entity-linking","display_name":"Entity linking","score":0.7138276100158691},{"id":"https://openalex.org/keywords/microblogging","display_name":"Microblogging","score":0.6628729701042175},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.6250528693199158},{"id":"https://openalex.org/keywords/benchmark","display_name":"Benchmark (surveying)","score":0.6158432960510254},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5965770483016968},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.586587131023407},{"id":"https://openalex.org/keywords/homophily","display_name":"Homophily","score":0.5301626324653625},{"id":"https://openalex.org/keywords/encoding","display_name":"Encoding (memory)","score":0.5100546479225159},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4693775177001953},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.44348227977752686},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.44134896993637085},{"id":"https://openalex.org/keywords/space","display_name":"Space (punctuation)","score":0.42567285895347595},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.42398664355278015},{"id":"https://openalex.org/keywords/knowledge-base","display_name":"Knowledge base","score":0.3724987506866455},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.26684844493865967},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07869464159011841}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7947285175323486},{"id":"https://openalex.org/C96711827","wikidata":"https://www.wikidata.org/wiki/Q17012245","display_name":"Entity linking","level":3,"score":0.7138276100158691},{"id":"https://openalex.org/C143275388","wikidata":"https://www.wikidata.org/wiki/Q92438","display_name":"Microblogging","level":3,"score":0.6628729701042175},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.6250528693199158},{"id":"https://openalex.org/C185798385","wikidata":"https://www.wikidata.org/wiki/Q1161707","display_name":"Benchmark (surveying)","level":2,"score":0.6158432960510254},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5965770483016968},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.586587131023407},{"id":"https://openalex.org/C2779812341","wikidata":"https://www.wikidata.org/wiki/Q5891525","display_name":"Homophily","level":2,"score":0.5301626324653625},{"id":"https://openalex.org/C125411270","wikidata":"https://www.wikidata.org/wiki/Q18653","display_name":"Encoding (memory)","level":2,"score":0.5100546479225159},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4693775177001953},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.44348227977752686},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.44134896993637085},{"id":"https://openalex.org/C2778572836","wikidata":"https://www.wikidata.org/wiki/Q380933","display_name":"Space (punctuation)","level":2,"score":0.42567285895347595},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.42398664355278015},{"id":"https://openalex.org/C4554734","wikidata":"https://www.wikidata.org/wiki/Q593744","display_name":"Knowledge base","level":2,"score":0.3724987506866455},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.26684844493865967},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07869464159011841},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C114614502","wikidata":"https://www.wikidata.org/wiki/Q76592","display_name":"Combinatorics","level":1,"score":0.0},{"id":"https://openalex.org/C13280743","wikidata":"https://www.wikidata.org/wiki/Q131089","display_name":"Geodesy","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.0},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/d16-1152","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d16-1152","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/d16-1152","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/d16-1152","pdf_url":null,"source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2016 Conference on Empirical Methods in Natural\n          Language Processing","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W86887328","https://openalex.org/W371426616","https://openalex.org/W1533230146","https://openalex.org/W1548663377","https://openalex.org/W1770543141","https://openalex.org/W1880262756","https://openalex.org/W1940500808","https://openalex.org/W2015186536","https://openalex.org/W2018165284","https://openalex.org/W2057047055","https://openalex.org/W2100341149","https://openalex.org/W2101196063","https://openalex.org/W2107474859","https://openalex.org/W2112896229","https://openalex.org/W2127426251","https://openalex.org/W2130354913","https://openalex.org/W2130495108","https://openalex.org/W2131753116","https://openalex.org/W2139694477","https://openalex.org/W2143570397","https://openalex.org/W2153579005","https://openalex.org/W2153848201","https://openalex.org/W2161066414","https://openalex.org/W2187561416","https://openalex.org/W2250387192","https://openalex.org/W2251079237","https://openalex.org/W2252231772","https://openalex.org/W2252241921","https://openalex.org/W2276263724","https://openalex.org/W2296194829","https://openalex.org/W3105705953"],"related_works":["https://openalex.org/W2250387192","https://openalex.org/W1541691357","https://openalex.org/W2090135255","https://openalex.org/W2168409722","https://openalex.org/W2026505290","https://openalex.org/W2782437235","https://openalex.org/W1993715838","https://openalex.org/W2359088421","https://openalex.org/W2515501281","https://openalex.org/W2181629536"],"abstract_inverted_index":{"Entity":[0],"linking":[1,13,144],"is":[2,23,30,114],"the":[3,66,75,93,142,161],"task":[4,22],"of":[5,8,46,60,77,96,153],"identifying":[6],"mentions":[7],"entities":[9,107],"in":[10,17,26,70,108,141],"text,":[11],"and":[12,87,106],"them":[14],"to":[15,34,57,91,160],"entries":[16],"a":[18,109,129],"knowledge":[19,48],"base.":[20],"This":[21],"especially":[24],"difficult":[25],"microblogs,":[27],"as":[28,158],"there":[29],"little":[31],"additional":[32],"text":[33],"provide":[35],"disambiguating":[36],"context;":[37],"rather,":[38],"authors":[39,119],"rely":[40],"on":[41,74,155],"an":[42],"implicit":[43,62],"common":[44],"ground":[45],"shared":[47],"with":[49],"their":[50],"readers.":[51],"In":[52],"this":[53,61,100],"paper,":[54],"we":[55],"attempt":[56],"capture":[58],"some":[59],"context":[63],"by":[64,102],"exploiting":[65],"social":[67],"network":[68],"structure":[69],"microblogs.":[71],"We":[72,98],"build":[73],"theory":[76],"homophily,":[78],"which":[79,113,134],"implies":[80],"that":[81,117,138],"socially":[82],"linked":[83],"individuals":[84],"share":[85],"interests,":[86],"are":[88,126,139],"therefore":[89],"likely":[90],"mention":[92],"same":[94],"sorts":[95],"entities.":[97],"implement":[99],"idea":[101],"encoding":[103],"authors,":[104],"mentions,":[105],"continuous":[110],"vector":[111,122],"space,":[112],"constructed":[115],"so":[116],"socially-connected":[118],"have":[120],"similar":[121],"representations.":[123],"These":[124],"vectors":[125],"incorporated":[127],"into":[128],"neural":[130],"structured":[131],"prediction":[132],"model,":[133],"captures":[135],"structural":[136],"constraints":[137],"inherent":[140],"entity":[143],"task.":[145],"Together,":[146],"these":[147],"design":[148],"decisions":[149],"yield":[150],"F1":[151],"improvements":[152],"1%-5%":[154],"benchmark":[156],"datasets,":[157],"compared":[159],"previous":[162],"state-of-the-art.":[163]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":6},{"year":2018,"cited_by_count":4},{"year":2017,"cited_by_count":3}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
