{"id":"https://openalex.org/W2990215670","doi":"https://doi.org/10.1007/s11192-019-03307-5","title":"Detecting bursty terms in computer science research","display_name":"Detecting bursty terms in computer science research","publication_year":2019,"publication_date":"2019-11-22","ids":{"openalex":"https://openalex.org/W2990215670","doi":"https://doi.org/10.1007/s11192-019-03307-5","mag":"2990215670"},"language":"en","primary_location":{"id":"doi:10.1007/s11192-019-03307-5","doi":"https://doi.org/10.1007/s11192-019-03307-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11192-019-03307-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11192-019-03307-5.pdf","source":{"id":"https://openalex.org/S148561398","display_name":"Scientometrics","issn_l":"0138-9130","issn":["0138-9130","1588-2861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","erih-plus","fnege-3","jufo-2","ki-jl-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320108","host_organization_name":"Springer Nature (Netherlands)","host_organization_lineage":["https://openalex.org/P4310320108","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature (Netherlands)","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientometrics","raw_type":"journal-article"},"volume":null,"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://link.springer.com/content/pdf/10.1007/s11192-019-03307-5.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5020283551","display_name":"Emma Tattershall","orcid":"https://orcid.org/0000-0001-5616-4002","observed_orcids":["https://orcid.org/0000-0001-5616-4002"]},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"E. Tattershall","raw_affiliation_strings":["Department of Computer Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK"],"raw_orcid":"https://orcid.org/0000-0001-5616-4002","affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5005912060","display_name":"Goran Nenadi\u0107","orcid":"https://orcid.org/0000-0003-0795-5363","observed_orcids":["https://orcid.org/0000-0003-0795-5363"]},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"G. Nenadic","raw_affiliation_strings":["Department of Computer Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK","institution_ids":["https://openalex.org/I28407311"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5049799218","display_name":"Robert Stevens","orcid":"https://orcid.org/0000-0002-6038-9025","observed_orcids":["https://orcid.org/0000-0002-6038-9025","https://orcid.org/0000-0002-3270-4040","https://orcid.org/0000-0002-7528-0102","https://orcid.org/0000-0001-6197-8414","https://orcid.org/0000-0001-5984-7837","https://orcid.org/0000-0003-3337-9910"]},"institutions":[{"id":"https://openalex.org/I28407311","display_name":"University of Manchester","ror":"https://ror.org/027m9bs27","country_code":"GB","type":"education","lineage":["https://openalex.org/I28407311"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"R. D. Stevens","raw_affiliation_strings":["Department of Computer Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Computer Science, The University of Manchester, Oxford Road, Manchester, M13 9PL, UK","institution_ids":["https://openalex.org/I28407311"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5020283551"],"corresponding_institution_ids":["https://openalex.org/I28407311"],"apc_list":{"value":2690,"currency":"USD","value_usd":2690},"apc_paid":{"value":2690,"currency":"USD","value_usd":2690},"fwci":1.6711,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":{"value":0.86790716,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":88,"max":98},"biblio":{"volume":"122","issue":"1","first_page":"681","last_page":"699"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10102","display_name":"scientometrics and bibliometrics research","score":0.9648000001907349,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10102","display_name":"scientometrics and bibliometrics research","score":0.9648000001907349,"subfield":{"id":"https://openalex.org/subfields/1804","display_name":"Statistics, Probability and Uncertainty"},"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.014800000004470348,"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/T13910","display_name":"Computational and Text Analysis Methods","score":0.004100000020116568,"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/research-trends","display_name":"research trends","score":0.5989999771118164},{"id":"https://openalex.org/keywords/computer-science-literature","display_name":"computer science literature","score":0.7210000157356262},{"id":"https://openalex.org/keywords/trend-detection","display_name":"trend detection","score":0.722000002861023},{"id":"https://openalex.org/keywords/text-classification","display_name":"text classification","score":0.5210000276565552},{"id":"https://openalex.org/keywords/research-topic-evolution","display_name":"research topic evolution","score":0.5339999794960022}],"concepts":[{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.8362603187561035},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8018712997436523},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.547021746635437},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.5247985124588013},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5164589881896973},{"id":"https://openalex.org/C110875604","wikidata":"https://www.wikidata.org/wiki/Q75","display_name":"The Internet","level":2,"score":0.5002262592315674},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.40189069509506226},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3574928343296051},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.20192810893058777},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1007/s11192-019-03307-5","doi":"https://doi.org/10.1007/s11192-019-03307-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11192-019-03307-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11192-019-03307-5.pdf","source":{"id":"https://openalex.org/S148561398","display_name":"Scientometrics","issn_l":"0138-9130","issn":["0138-9130","1588-2861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","erih-plus","fnege-3","jufo-2","ki-jl-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320108","host_organization_name":"Springer Nature (Netherlands)","host_organization_lineage":["https://openalex.org/P4310320108","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature (Netherlands)","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientometrics","raw_type":"journal-article"},{"id":"pmh:oai:RePEc:spr:scient:v:122:y:2020:i:1:d:10.1007_s11192-019-03307-5","doi":null,"is_oa":false,"landing_page_url":"http://link.springer.com/10.1007/s11192-019-03307-5","pdf_url":null,"source":{"id":"https://openalex.org/S4306401271","display_name":"RePEc: Research Papers in Economics","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I77793887","host_organization_name":"Federal Reserve Bank of St. Louis","host_organization_lineage":["https://openalex.org/I77793887"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"article"},{"id":"pmh:oai:pure.atira.dk:openaire_cris_publications/65e3dd23-b1c5-4c64-8abe-6a67ce98f9b8","doi":null,"is_oa":true,"landing_page_url":"https://research.manchester.ac.uk/en/publications/65e3dd23-b1c5-4c64-8abe-6a67ce98f9b8","pdf_url":null,"source":{"id":"https://openalex.org/S4306400662","display_name":"Research Explorer (The University of Manchester)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":"https://openalex.org/I28407311","host_organization_name":"University of Manchester","host_organization_lineage":["https://openalex.org/I28407311"],"host_organization_lineage_names":[],"type":"repository"},"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Tattershall, E, Nenadic, G & Stevens, R 2019, 'Detecting bursty terms in computer science research', Scientometrics. https://doi.org/10.1007/s11192-019-03307-5","raw_type":"info:eu-repo/semantics/article"}],"best_oa_location":{"id":"doi:10.1007/s11192-019-03307-5","doi":"https://doi.org/10.1007/s11192-019-03307-5","is_oa":true,"landing_page_url":"https://doi.org/10.1007/s11192-019-03307-5","pdf_url":"https://link.springer.com/content/pdf/10.1007/s11192-019-03307-5.pdf","source":{"id":"https://openalex.org/S148561398","display_name":"Scientometrics","issn_l":"0138-9130","issn":["0138-9130","1588-2861"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["abdc-a","anvur-class-a","anvur-scientific","cwts-core","erih-plus","fnege-3","jufo-2","ki-jl-1","norway-1","poland-100","russia-white-list-1","vabb-shw"],"host_organization":"https://openalex.org/P4310320108","host_organization_name":"Springer Nature (Netherlands)","host_organization_lineage":["https://openalex.org/P4310320108","https://openalex.org/P4310319965"],"host_organization_lineage_names":["Springer Nature (Netherlands)","Springer Nature"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Scientometrics","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[{"id":"https://openalex.org/G4082175093","display_name":"Manchester Centre for Doctoral Training in Computer Science","funder_award_id":"EP/I028099/1","funder_id":"https://openalex.org/F4320334627","funder_display_name":"Engineering and Physical Sciences Research Council"}],"funders":[{"id":"https://openalex.org/F4320334627","display_name":"Engineering and Physical Sciences Research Council","ror":"https://ror.org/0439y7842"}],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2990215670.pdf","grobid_xml":"https://content.openalex.org/works/W2990215670.grobid-xml"},"referenced_works_count":30,"referenced_works":["https://openalex.org/W183265497","https://openalex.org/W315818910","https://openalex.org/W424762967","https://openalex.org/W579623069","https://openalex.org/W1498436455","https://openalex.org/W1521626219","https://openalex.org/W1880262756","https://openalex.org/W1898724844","https://openalex.org/W1907286193","https://openalex.org/W1977401594","https://openalex.org/W1984471046","https://openalex.org/W2001082470","https://openalex.org/W2009136420","https://openalex.org/W2018165284","https://openalex.org/W2026302857","https://openalex.org/W2040466507","https://openalex.org/W2044738244","https://openalex.org/W2109154616","https://openalex.org/W2117681292","https://openalex.org/W2134866961","https://openalex.org/W2135909747","https://openalex.org/W2137553870","https://openalex.org/W2163605009","https://openalex.org/W2165231903","https://openalex.org/W2514454423","https://openalex.org/W2613214602","https://openalex.org/W2783373068","https://openalex.org/W2790808809","https://openalex.org/W2843582094","https://openalex.org/W3107452630"],"related_works":["https://openalex.org/W2731631740","https://openalex.org/W2079306005","https://openalex.org/W4310113574","https://openalex.org/W7214956221","https://openalex.org/W1480409551","https://openalex.org/W3151923767","https://openalex.org/W7128505044","https://openalex.org/W2087120281","https://openalex.org/W2992034055","https://openalex.org/W7119308934"],"abstract_inverted_index":{"Abstract":[0],"Research":[1],"topics":[2,18],"rise":[3,136],"and":[4,30,38,68,108,122,166,170],"fall":[5,138],"in":[6,42,86,98,111,139,141,146],"popularity":[7,140],"over":[8,53,72],"time,":[9],"some":[10],"more":[11],"swiftly":[12],"than":[13],"others.":[14],"The":[15,151],"fastest":[16],"rising":[17],"are":[19],"typically":[20],"called":[21],"bursts;":[22],"for":[23],"example":[24],"\u201cdeep":[25],"learning\u201d,":[26],"\u201cinternet":[27],"of":[28,75,83,92,106,119,149,161],"things\u201d":[29],"\u201cbig":[31],"data\u201d.":[32],"Being":[33],"able":[34],"to":[35,71,127,131,157,163],"automatically":[36],"detect":[37],"track":[39],"bursty":[40,120,168],"terms":[41,169],"the":[43,81,87,90,103,142,147],"literature":[44],"could":[45],"give":[46],"insight":[47],"into":[48],"how":[49],"scientific":[50],"thought":[51],"evolves":[52],"time.":[54],"In":[55],"this":[56,99],"paper,":[57],"we":[58,101],"take":[59],"a":[60,93,112,117,129],"trend":[61],"detection":[62],"algorithm":[63],"from":[64],"stock":[65],"market":[66],"analysis":[67],"apply":[69],"it":[70],"30":[73],"years":[74],"computer":[76],"science":[77],"research":[78],"abstracts,":[79],"treating":[80],"prevalence":[82],"each":[84],"term":[85],"dataset":[88],"like":[89],"price":[91],"stock.":[94],"Unlike":[95],"previous":[96],"work":[97],"domain,":[100],"use":[102,124],"free":[104],"text":[105,162],"abstracts":[107],"titles,":[109],"resulting":[110],"finer-grained":[113],"analysis.":[114],"We":[115],"report":[116],"list":[118],"terms,":[121],"then":[123],"historical":[125],"data":[126],"build":[128],"classifier":[130],"predict":[132,171],"whether":[133],"they":[134],"will":[135],"or":[137],"future,":[143],"obtaining":[144],"accuracy":[145],"region":[148],"80%.":[150],"proposed":[152],"methodology":[153],"can":[154],"be":[155],"applied":[156],"any":[158],"time-ordered":[159],"collection":[160],"yield":[164],"past":[165],"present":[167],"their":[172],"probable":[173],"fate.":[174]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":3},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":1}],"updated_date":"2026-10-29T09:56:32.521200","created_date":"2019-12-05T00:00:00"}