{"id":"https://openalex.org/W1978660644","doi":"https://doi.org/10.1145/2502069.2502073","title":"Enhancing sentiment extraction from text by means of arguments","display_name":"Enhancing sentiment extraction from text by means of arguments","publication_year":2013,"publication_date":"2013-08-01","ids":{"openalex":"https://openalex.org/W1978660644","doi":"https://doi.org/10.1145/2502069.2502073","mag":"1978660644"},"language":"en","primary_location":{"id":"doi:10.1145/2502069.2502073","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2502069.2502073","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining","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/A5066205519","display_name":"Lucas Carstens","orcid":null},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Lucas Carstens","raw_affiliation_strings":["Imperial College London, London, UK","#N#Imperial College London, London, UK"],"affiliations":[{"raw_affiliation_string":"Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"#N#Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078354590","display_name":"Francesca Toni","orcid":"https://orcid.org/0000-0001-8194-1459"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Francesca Toni","raw_affiliation_strings":["Imperial College London, London, UK","#N#Imperial College London, London, UK"],"affiliations":[{"raw_affiliation_string":"Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]},{"raw_affiliation_string":"#N#Imperial College London, London, UK","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5066205519"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.05871865,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"9"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T10664","display_name":"Sentiment Analysis and Opinion Mining","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/T10028","display_name":"Topic Modeling","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":0.9994999766349792,"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/support-vector-machine","display_name":"Support vector machine","score":0.8690884113311768},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.83788001537323},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7224660515785217},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6995273232460022},{"id":"https://openalex.org/keywords/polarity","display_name":"Polarity (international relations)","score":0.6629596948623657},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.5380755066871643},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5056560039520264},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.462067186832428},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3520227372646332}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.8690884113311768},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.83788001537323},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7224660515785217},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6995273232460022},{"id":"https://openalex.org/C2777361361","wikidata":"https://www.wikidata.org/wiki/Q1112585","display_name":"Polarity (international relations)","level":3,"score":0.6629596948623657},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.5380755066871643},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5056560039520264},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.462067186832428},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3520227372646332},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C54355233","wikidata":"https://www.wikidata.org/wiki/Q7162","display_name":"Genetics","level":1,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C1491633281","wikidata":"https://www.wikidata.org/wiki/Q7868","display_name":"Cell","level":2,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/2502069.2502073","is_oa":false,"landing_page_url":"https://doi.org/10.1145/2502069.2502073","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the Second International Workshop on Issues of Sentiment Discovery and Opinion Mining","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Peace, Justice and strong institutions","id":"https://metadata.un.org/sdg/16","score":0.5400000214576721},{"display_name":"Reduced inequalities","id":"https://metadata.un.org/sdg/10","score":0.4099999964237213}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":37,"referenced_works":["https://openalex.org/W38739846","https://openalex.org/W50950926","https://openalex.org/W142730124","https://openalex.org/W143775383","https://openalex.org/W187432112","https://openalex.org/W1503333931","https://openalex.org/W1506806321","https://openalex.org/W1663973292","https://openalex.org/W1965944404","https://openalex.org/W1991224572","https://openalex.org/W2014902591","https://openalex.org/W2017238344","https://openalex.org/W2034120077","https://openalex.org/W2038507439","https://openalex.org/W2057577760","https://openalex.org/W2080558111","https://openalex.org/W2081580037","https://openalex.org/W2094728533","https://openalex.org/W2097726431","https://openalex.org/W2104540263","https://openalex.org/W2108287887","https://openalex.org/W2112422413","https://openalex.org/W2114524997","https://openalex.org/W2115023510","https://openalex.org/W2121835362","https://openalex.org/W2126581182","https://openalex.org/W2136000097","https://openalex.org/W2136140395","https://openalex.org/W2149167588","https://openalex.org/W2160052288","https://openalex.org/W2166706824","https://openalex.org/W2436001372","https://openalex.org/W2912804155","https://openalex.org/W3017975492","https://openalex.org/W3105439152","https://openalex.org/W4205184193","https://openalex.org/W6678923525"],"related_works":["https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2400337198","https://openalex.org/W2354902965","https://openalex.org/W2596247554","https://openalex.org/W4301373556","https://openalex.org/W3132372214","https://openalex.org/W4224284088","https://openalex.org/W1984947604"],"abstract_inverted_index":{"Sentiment":[0,90],"Analysis":[1,91],"is":[2],"concerned":[3],"with":[4,52,103],"(1)":[5,29],"differentiating":[6],"opinionated":[7,17,47],"text":[8,11,48,51,118],"from":[9,49],"factual":[10],"and,":[12],"in":[13,92,142],"the":[14,44,53,76,86],"case":[15],"of":[16,46,55,67,88,116,127,131,135,145],"text,":[18],"(2)":[19],"determine":[20],"its":[21],"polarity.":[22],"With":[23],"this":[24,93],"paper,":[25],"we":[26],"address":[27],"problem":[28],"and":[30,61,72,119],"present":[31],"A-SVM":[32],"(Argument":[33],"enhanced":[34],"Support":[35,57],"Vector":[36,58],"Machines),":[37],"a":[38,68,82,113,132],"multimodal":[39,105],"system":[40,106],"that":[41,126],"focuses":[42],"on":[43],"discrimination":[45],"non-opinionated":[50],"help":[54],"(i)":[56],"Machines":[59],"(SVM)":[60],"(ii)":[62],"arguments,":[63],"acquired":[64],"by":[65,97],"means":[66],"user":[69],"feedback":[70],"mechanism,":[71],"used":[73,81],"to":[74,84,125],"improve":[75],"SVM":[77],"classifications.":[78],"We":[79],"have":[80],"prototype":[83],"investigate":[85],"validity":[87],"approaching":[89],"multi":[94],"faceted":[95],"manner":[96],"comparing":[98],"straightforward":[99],"Machine":[100],"Learning":[101],"techniques":[102],"our":[104],"architecture.":[107],"All":[108],"evaluations":[109],"were":[110],"executed":[111],"using":[112],"purpose-built":[114],"corpus":[115],"annotated":[117],"A-SVM's":[120],"classification":[121,130,143],"performance":[122],"was":[123],"compared":[124],"SVM.":[128],"The":[129],"test":[133],"set":[134],"approximately":[136],"4,500":[137],"n-grams":[138],"yielded":[139],"an":[140],"increase":[141],"precision":[144],"5.6%.":[146]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
