{"id":"https://openalex.org/W2770760637","doi":"https://doi.org/10.1109/taffc.2017.2777842","title":"Idiom-Based Features in Sentiment Analysis: Cutting the Gordian Knot","display_name":"Idiom-Based Features in Sentiment Analysis: Cutting the Gordian Knot","publication_year":2017,"publication_date":"2017-12-19","ids":{"openalex":"https://openalex.org/W2770760637","doi":"https://doi.org/10.1109/taffc.2017.2777842","mag":"2770760637"},"language":"en","primary_location":{"id":"doi:10.1109/taffc.2017.2777842","is_oa":true,"landing_page_url":"https://doi.org/10.1109/taffc.2017.2777842","pdf_url":"https://ieeexplore.ieee.org/ielx7/5165369/9103669/08226982.pdf","source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://ieeexplore.ieee.org/ielx7/5165369/9103669/08226982.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5016345745","display_name":"\u202aIrena Spasi\u0107","orcid":"https://orcid.org/0000-0002-8132-3885"},"institutions":[{"id":"https://openalex.org/I79510175","display_name":"Cardiff University","ror":"https://ror.org/03kk7td41","country_code":"GB","type":"education","lineage":["https://openalex.org/I79510175"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Irena Spasic","raw_affiliation_strings":["School of Computer Science & Informatics, Cardiff University, Cardiff, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0002-8132-3885","affiliations":[{"raw_affiliation_string":"School of Computer Science & Informatics, Cardiff University, Cardiff, United Kingdom","institution_ids":["https://openalex.org/I79510175"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043580907","display_name":"Lowri Williams","orcid":"https://orcid.org/0000-0002-3794-6145"},"institutions":[{"id":"https://openalex.org/I79510175","display_name":"Cardiff University","ror":"https://ror.org/03kk7td41","country_code":"GB","type":"education","lineage":["https://openalex.org/I79510175"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Lowri Williams","raw_affiliation_strings":["School of Computer Science & Informatics, Cardiff University, Cardiff, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0002-3794-6145","affiliations":[{"raw_affiliation_string":"School of Computer Science & Informatics, Cardiff University, Cardiff, United Kingdom","institution_ids":["https://openalex.org/I79510175"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065966118","display_name":"Andreas Buerki","orcid":"https://orcid.org/0000-0003-2151-3246"},"institutions":[{"id":"https://openalex.org/I79510175","display_name":"Cardiff University","ror":"https://ror.org/03kk7td41","country_code":"GB","type":"education","lineage":["https://openalex.org/I79510175"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Andreas Buerki","raw_affiliation_strings":["School of English, Communication and Philosophy, Cardiff University, Cardiff, United Kingdom"],"raw_orcid":"https://orcid.org/0000-0003-2151-3246","affiliations":[{"raw_affiliation_string":"School of English, Communication and Philosophy, Cardiff University, Cardiff, United Kingdom","institution_ids":["https://openalex.org/I79510175"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I79510175"],"apc_list":null,"apc_paid":null,"fwci":0.826,"has_fulltext":true,"cited_by_count":21,"citation_normalized_percentile":{"value":0.81395034,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":99},"biblio":{"volume":"11","issue":"2","first_page":"189","last_page":"199"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9987000226974487,"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/T10028","display_name":"Topic Modeling","score":0.9976000189781189,"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":0.7682730555534363},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7471948266029358},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6486489772796631},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6251471638679504},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5743656158447266},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5523545742034912},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.5387824773788452},{"id":"https://openalex.org/keywords/baseline","display_name":"Baseline (sea)","score":0.5144903659820557},{"id":"https://openalex.org/keywords/overhead","display_name":"Overhead (engineering)","score":0.45786431431770325},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.44397684931755066},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.36621272563934326},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2904573678970337},{"id":"https://openalex.org/keywords/programming-language","display_name":"Programming language","score":0.13155525922775269}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7682730555534363},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7471948266029358},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6486489772796631},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6251471638679504},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5743656158447266},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5523545742034912},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.5387824773788452},{"id":"https://openalex.org/C12725497","wikidata":"https://www.wikidata.org/wiki/Q810247","display_name":"Baseline (sea)","level":2,"score":0.5144903659820557},{"id":"https://openalex.org/C2779960059","wikidata":"https://www.wikidata.org/wiki/Q7113681","display_name":"Overhead (engineering)","level":2,"score":0.45786431431770325},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.44397684931755066},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.36621272563934326},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2904573678970337},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.13155525922775269},{"id":"https://openalex.org/C111368507","wikidata":"https://www.wikidata.org/wiki/Q43518","display_name":"Oceanography","level":1,"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/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","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":2,"locations":[{"id":"doi:10.1109/taffc.2017.2777842","is_oa":true,"landing_page_url":"https://doi.org/10.1109/taffc.2017.2777842","pdf_url":"https://ieeexplore.ieee.org/ielx7/5165369/9103669/08226982.pdf","source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"},{"id":"pmh:oai:https://orca.cardiff.ac.uk:106926","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306401195","display_name":"ORCA Online Research @Cardiff (Cardiff University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I79510175","host_organization_name":"Cardiff University","host_organization_lineage":["https://openalex.org/I79510175"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"acceptedVersion","is_accepted":true,"is_published":false,"raw_source_name":"","raw_type":"Article"}],"best_oa_location":{"id":"doi:10.1109/taffc.2017.2777842","is_oa":true,"landing_page_url":"https://doi.org/10.1109/taffc.2017.2777842","pdf_url":"https://ieeexplore.ieee.org/ielx7/5165369/9103669/08226982.pdf","source":{"id":"https://openalex.org/S104780363","display_name":"IEEE Transactions on Affective Computing","issn_l":"1949-3045","issn":["1949-3045","2371-9850"],"is_oa":false,"is_in_doaj":false,"is_core":true,"host_organization":"https://openalex.org/P4310319808","host_organization_name":"Institute of Electrical and Electronics Engineers","host_organization_lineage":["https://openalex.org/P4310319808"],"host_organization_lineage_names":["Institute of Electrical and Electronics Engineers"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IEEE Transactions on Affective Computing","raw_type":"journal-article"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.8199999928474426}],"awards":[{"id":"https://openalex.org/G7652010843","display_name":null,"funder_award_id":"1511905","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":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2770760637.pdf","grobid_xml":"https://content.openalex.org/works/W2770760637.grobid-xml"},"referenced_works_count":93,"referenced_works":["https://openalex.org/W13254153","https://openalex.org/W103204726","https://openalex.org/W134039547","https://openalex.org/W145806832","https://openalex.org/W172541218","https://openalex.org/W630286854","https://openalex.org/W650288370","https://openalex.org/W1498763386","https://openalex.org/W1502101714","https://openalex.org/W1503951804","https://openalex.org/W1513756337","https://openalex.org/W1574901103","https://openalex.org/W1595459570","https://openalex.org/W1719006806","https://openalex.org/W1940872118","https://openalex.org/W1951269370","https://openalex.org/W1970381522","https://openalex.org/W1971218560","https://openalex.org/W2002391613","https://openalex.org/W2005311637","https://openalex.org/W2026451606","https://openalex.org/W2034511503","https://openalex.org/W2034995091","https://openalex.org/W2037789405","https://openalex.org/W2040467972","https://openalex.org/W2053154970","https://openalex.org/W2069395416","https://openalex.org/W2071956453","https://openalex.org/W2075928407","https://openalex.org/W2078906720","https://openalex.org/W2079004251","https://openalex.org/W2079521622","https://openalex.org/W2079547420","https://openalex.org/W2081580037","https://openalex.org/W2090860222","https://openalex.org/W2096333412","https://openalex.org/W2098057602","https://openalex.org/W2100483895","https://openalex.org/W2102134623","https://openalex.org/W2112422413","https://openalex.org/W2113143819","https://openalex.org/W2116394855","https://openalex.org/W2118202495","https://openalex.org/W2120578583","https://openalex.org/W2123215530","https://openalex.org/W2131305515","https://openalex.org/W2132232498","https://openalex.org/W2133990480","https://openalex.org/W2138928235","https://openalex.org/W2141179513","https://openalex.org/W2146111747","https://openalex.org/W2149340438","https://openalex.org/W2160408828","https://openalex.org/W2168625136","https://openalex.org/W2189662395","https://openalex.org/W2224490803","https://openalex.org/W2251026193","https://openalex.org/W2251939518","https://openalex.org/W2402668809","https://openalex.org/W2471072780","https://openalex.org/W2500582059","https://openalex.org/W2517996181","https://openalex.org/W2563836118","https://openalex.org/W2594108681","https://openalex.org/W2787893582","https://openalex.org/W2797597138","https://openalex.org/W2925907129","https://openalex.org/W2964020032","https://openalex.org/W2970620451","https://openalex.org/W3152231500","https://openalex.org/W4233906183","https://openalex.org/W4239946314","https://openalex.org/W4246644428","https://openalex.org/W4250317401","https://openalex.org/W4388119441","https://openalex.org/W4388152942","https://openalex.org/W6600530165","https://openalex.org/W6604179135","https://openalex.org/W6605455466","https://openalex.org/W6605892302","https://openalex.org/W6630298364","https://openalex.org/W6630842240","https://openalex.org/W6635262639","https://openalex.org/W6640362995","https://openalex.org/W6640624132","https://openalex.org/W6674485571","https://openalex.org/W6677093621","https://openalex.org/W6683496849","https://openalex.org/W6685465864","https://openalex.org/W6687724439","https://openalex.org/W6691459498","https://openalex.org/W6691668045","https://openalex.org/W6712930306"],"related_works":["https://openalex.org/W2383111961","https://openalex.org/W2365952365","https://openalex.org/W2352448290","https://openalex.org/W2380820513","https://openalex.org/W2913146933","https://openalex.org/W2372385138","https://openalex.org/W4296359239","https://openalex.org/W2101155126","https://openalex.org/W2548633793","https://openalex.org/W2043093291"],"abstract_inverted_index":{"In":[0],"this":[1,169],"paper":[2],"we":[3,16],"describe":[4],"an":[5,77,156],"automated":[6,17,104],"approach":[7,105],"to":[8,33,70],"enriching":[9],"sentiment":[10,41,85],"analysis":[11,86],"with":[12,134,168],"idiom-based":[13],"features.":[14],"Specifically,":[15],"the":[18,21,72,83,95,107,116,123,131,135,142,162,174],"development":[19],"of":[20,30,144,159],"supporting":[22],"lexico-semantic":[23],"resources,":[24,56],"which":[25,50,80],"include":[26],"(1)":[27],"a":[28,149],"set":[29],"rules":[31],"used":[32,69],"identify":[34],"idioms":[35,160],"in":[36,76,148],"text":[37],"and":[38],"(2)":[39],"their":[40],"polarity":[42],"classifications.":[43],"Our":[44],"method":[45],"demonstrates":[46],"how":[47],"idiom":[48],"dictionaries,":[49],"are":[51],"readily":[52,154],"available":[53],"general":[54,147],"pedagogical":[55],"can":[57,153],"be":[58],"adapted":[59],"into":[60,99,120],"purpose-specific":[61],"computational":[62],"resources":[63,66],"automatically.":[64],"These":[65],"were":[67],"then":[68],"replace":[71],"manually":[73,136],"engineered":[74,137],"counterparts":[75],"existing":[78],"system,":[79],"originally":[81],"outperformed":[82,106],"baseline":[84],"approaches":[87],"by":[88,109],"17":[89],"percentage":[90,111],"points":[91,112],"on":[92,113],"average,":[93],"taking":[94,115],"F-measure":[96,117],"from":[97,118],"40s":[98,119],"60s.":[100],"The":[101],"new":[102],"fully":[103,172],"baselines":[108],"8":[110],"average":[114],"50s.":[121],"Although":[122],"latter":[124],"improvement":[125],"is":[126],"not":[127],"as":[128,130],"high":[129],"one":[132],"achieved":[133],"features,":[138],"it":[139,152],"has":[140],"got":[141],"advantage":[143],"being":[145],"more":[146],"sense":[150],"that":[151],"utilize":[155],"arbitrary":[157],"list":[158],"without":[161],"knowledge":[163],"acquisition":[164],"overhead":[165],"previously":[166],"associated":[167],"task,":[170],"thereby":[171],"automating":[173],"original":[175],"approach.":[176]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":5},{"year":2021,"cited_by_count":8},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2016,"cited_by_count":1}],"updated_date":"2026-06-26T08:34:08.712188","created_date":"2025-10-10T00:00:00"}