{"id":"https://openalex.org/W2113552117","doi":"https://doi.org/10.3115/v1/d14-1194","title":"#TagSpace: Semantic Embeddings from Hashtags","display_name":"#TagSpace: Semantic Embeddings from Hashtags","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2113552117","doi":"https://doi.org/10.3115/v1/d14-1194","mag":"2113552117"},"language":"en","primary_location":{"id":"doi:10.3115/v1/d14-1194","is_oa":false,"landing_page_url":"https://doi.org/10.3115/v1/d14-1194","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"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/A5076635608","display_name":"Jason Weston","orcid":null},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":true,"raw_author_name":"Jason Weston","raw_affiliation_strings":["Facebook"],"affiliations":[{"raw_affiliation_string":"Facebook","institution_ids":["https://openalex.org/I2252078561"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5078511139","display_name":"Sumit Chopra","orcid":"https://orcid.org/0009-0009-6637-2230"},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Sumit Chopra","raw_affiliation_strings":["Facebook"],"affiliations":[{"raw_affiliation_string":"Facebook","institution_ids":["https://openalex.org/I2252078561"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5000717555","display_name":"Keith Adams","orcid":null},"institutions":[{"id":"https://openalex.org/I2252078561","display_name":"Meta (Israel)","ror":"https://ror.org/02388em19","country_code":"IL","type":"company","lineage":["https://openalex.org/I2252078561","https://openalex.org/I4210114444"]}],"countries":["IL"],"is_corresponding":false,"raw_author_name":"Keith Adams","raw_affiliation_strings":["Facebook"],"affiliations":[{"raw_affiliation_string":"Facebook","institution_ids":["https://openalex.org/I2252078561"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5076635608"],"corresponding_institution_ids":["https://openalex.org/I2252078561"],"apc_list":null,"apc_paid":null,"fwci":24.9483,"has_fulltext":false,"cited_by_count":171,"citation_normalized_percentile":{"value":0.99581555,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":94,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"1822","last_page":"1827"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":1.0,"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":1.0,"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/T10181","display_name":"Natural Language Processing Techniques","score":0.9995999932289124,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9990000128746033,"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":0.8825708627700806},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7653489112854004},{"id":"https://openalex.org/keywords/convolutional-neural-network","display_name":"Convolutional neural network","score":0.7143594026565552},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7038244605064392},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.6531932353973389},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6518428325653076},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.6247329711914062},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4501398503780365},{"id":"https://openalex.org/keywords/semantic-feature","display_name":"Semantic feature","score":0.4119637906551361},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3470345139503479}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8825708627700806},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7653489112854004},{"id":"https://openalex.org/C81363708","wikidata":"https://www.wikidata.org/wiki/Q17084460","display_name":"Convolutional neural network","level":2,"score":0.7143594026565552},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7038244605064392},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.6531932353973389},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6518428325653076},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.6247329711914062},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4501398503780365},{"id":"https://openalex.org/C2781122975","wikidata":"https://www.wikidata.org/wiki/Q16928266","display_name":"Semantic feature","level":2,"score":0.4119637906551361},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3470345139503479},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"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":3,"locations":[{"id":"doi:10.3115/v1/d14-1194","is_oa":false,"landing_page_url":"https://doi.org/10.3115/v1/d14-1194","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2014 Conference on Empirical Methods in Natural Language Processing (EMNLP)","raw_type":"proceedings-article"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.668.2094","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.668.2094","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://aclweb.org/anthology/D/D14/D14-1194.pdf","raw_type":"text"},{"id":"pmh:oai:CiteSeerX.psu:10.1.1.671.2248","is_oa":false,"landing_page_url":"http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.671.2248","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"http://emnlp2014.org/papers/pdf/EMNLP2014194.pdf","raw_type":"text"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.5799999833106995,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":18,"referenced_works":["https://openalex.org/W21006490","https://openalex.org/W71795751","https://openalex.org/W91766825","https://openalex.org/W98255950","https://openalex.org/W100623710","https://openalex.org/W1553232534","https://openalex.org/W1614298861","https://openalex.org/W2112251034","https://openalex.org/W2138243089","https://openalex.org/W2147152072","https://openalex.org/W2151166364","https://openalex.org/W2158139315","https://openalex.org/W2158899491","https://openalex.org/W2168963845","https://openalex.org/W2250475089","https://openalex.org/W2251939518","https://openalex.org/W2951723246","https://openalex.org/W2951781666"],"related_works":["https://openalex.org/W2364155688","https://openalex.org/W2046522763","https://openalex.org/W2366916257","https://openalex.org/W2375847997","https://openalex.org/W2072836406","https://openalex.org/W2391772185","https://openalex.org/W2061641547","https://openalex.org/W4386420450","https://openalex.org/W2355099127","https://openalex.org/W2361892564"],"abstract_inverted_index":{"We":[0],"describe":[1],"a":[2,17,72,80],"convolutional":[3],"neural":[4],"net-work":[5],"that":[6,48,66],"learns":[7],"feature":[8],"representations":[9],"for":[10,60],"short":[11],"textual":[12],"posts":[13],"using":[14],"hashtags":[15],"as":[16,37,63],"su-pervised":[18],"signal.":[19],"The":[20],"proposed":[21],"approach":[22],"is":[23,58],"trained":[24],"on":[25,40,71],"up":[26],"to":[27],"5.5":[28],"billion":[29],"words":[30],"predict-ing":[31],"100,000":[32],"possible":[33],"hashtags.":[34],"As":[35],"well":[36],"strong":[38],"performance":[39],"the":[41,55],"hashtag":[42],"predic-tion":[43],"task":[44],"itself,":[45],"we":[46,68],"show":[47],"its":[49],"learned":[50],"representation":[51],"of":[52,82],"text":[53],"(ignoring":[54],"hash-tag":[56],"labels)":[57],"useful":[59],"other":[61],"tasks":[62],"well.":[64],"To":[65],"end,":[67],"present":[69],"results":[70],"docu-ment":[73],"recommendation":[74],"task,":[75],"where":[76],"it":[77],"also":[78],"outperforms":[79],"number":[81],"baselines.":[83],"1":[84]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":3},{"year":2023,"cited_by_count":7},{"year":2022,"cited_by_count":8},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":21},{"year":2019,"cited_by_count":33},{"year":2018,"cited_by_count":24},{"year":2017,"cited_by_count":20},{"year":2016,"cited_by_count":24},{"year":2015,"cited_by_count":13},{"year":2014,"cited_by_count":2}],"updated_date":"2026-04-05T17:49:38.594831","created_date":"2025-10-10T00:00:00"}