{"id":"https://openalex.org/W2251740185","doi":"https://doi.org/10.18653/v1/s15-2119","title":"UPF-taln: SemEval 2015 Tasks 10 and 11. Sentiment Analysis of Literal and Figurative Language in Twitter","display_name":"UPF-taln: SemEval 2015 Tasks 10 and 11. Sentiment Analysis of Literal and Figurative Language in Twitter","publication_year":2015,"publication_date":"2015-01-01","ids":{"openalex":"https://openalex.org/W2251740185","doi":"https://doi.org/10.18653/v1/s15-2119","mag":"2251740185"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s15-2119","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s15-2119","pdf_url":"https://www.aclweb.org/anthology/S15-2119.pdf","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 9th International Workshop on Semantic Evaluation (SemEval 2015)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/S15-2119.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5102984496","display_name":"Francesco Barbieri","orcid":"https://orcid.org/0000-0002-2144-8440"},"institutions":[{"id":"https://openalex.org/I170486558","display_name":"Pompeu Fabra University","ror":"https://ror.org/04n0g0b29","country_code":"ES","type":"education","lineage":["https://openalex.org/I170486558"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Francesco Barbieri","raw_affiliation_strings":["Universitat Pompeu Fabra, Barcelona, Spain"],"affiliations":[{"raw_affiliation_string":"Universitat Pompeu Fabra, Barcelona, Spain","institution_ids":["https://openalex.org/I170486558"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5077327085","display_name":"Francesco Ronzano","orcid":"https://orcid.org/0000-0001-5037-9061"},"institutions":[{"id":"https://openalex.org/I170486558","display_name":"Pompeu Fabra University","ror":"https://ror.org/04n0g0b29","country_code":"ES","type":"education","lineage":["https://openalex.org/I170486558"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Francesco Ronzano","raw_affiliation_strings":["Universitat Pompeu Fabra, Barcelona, Spain"],"affiliations":[{"raw_affiliation_string":"Universitat Pompeu Fabra, Barcelona, Spain","institution_ids":["https://openalex.org/I170486558"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5046825099","display_name":"Horacio Saggion","orcid":"https://orcid.org/0000-0003-0016-7807"},"institutions":[{"id":"https://openalex.org/I170486558","display_name":"Pompeu Fabra University","ror":"https://ror.org/04n0g0b29","country_code":"ES","type":"education","lineage":["https://openalex.org/I170486558"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Horacio Saggion","raw_affiliation_strings":["Universitat Pompeu Fabra, Barcelona, Spain"],"affiliations":[{"raw_affiliation_string":"Universitat Pompeu Fabra, Barcelona, Spain","institution_ids":["https://openalex.org/I170486558"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102984496"],"corresponding_institution_ids":["https://openalex.org/I170486558"],"apc_list":null,"apc_paid":null,"fwci":2.1572,"has_fulltext":true,"cited_by_count":16,"citation_normalized_percentile":{"value":0.90494011,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"704","last_page":"708"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998000264167786,"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":0.9998000264167786,"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":0.9980000257492065,"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":0.9979000091552734,"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/semeval","display_name":"SemEval","score":0.9180458784103394},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8267954587936401},{"id":"https://openalex.org/keywords/literal-and-figurative-language","display_name":"Literal and figurative language","score":0.8034124970436096},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7596059441566467},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.7329055666923523},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6904834508895874},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.680383563041687},{"id":"https://openalex.org/keywords/literal","display_name":"Literal (mathematical logic)","score":0.6396256685256958},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.6367186903953552},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.5449045300483704},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.4554649293422699},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1472078561782837},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.09861400723457336},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.08815857768058777}],"concepts":[{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.9180458784103394},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8267954587936401},{"id":"https://openalex.org/C46182478","wikidata":"https://www.wikidata.org/wiki/Q7363315","display_name":"Literal and figurative language","level":2,"score":0.8034124970436096},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7596059441566467},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7329055666923523},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6904834508895874},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.680383563041687},{"id":"https://openalex.org/C2780882242","wikidata":"https://www.wikidata.org/wiki/Q14235582","display_name":"Literal (mathematical logic)","level":2,"score":0.6396256685256958},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.6367186903953552},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.5449045300483704},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.4554649293422699},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1472078561782837},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.09861400723457336},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.08815857768058777},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","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/s15-2119","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s15-2119","pdf_url":"https://www.aclweb.org/anthology/S15-2119.pdf","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 9th International Workshop on Semantic Evaluation (SemEval 2015)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/s15-2119","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s15-2119","pdf_url":"https://www.aclweb.org/anthology/S15-2119.pdf","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 9th International Workshop on Semantic Evaluation (SemEval 2015)","raw_type":"proceedings-article"},"sustainable_development_goals":[{"score":0.49000000953674316,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2251740185.pdf","grobid_xml":"https://content.openalex.org/works/W2251740185.grobid-xml"},"referenced_works_count":18,"referenced_works":["https://openalex.org/W193524605","https://openalex.org/W1512098439","https://openalex.org/W1521125545","https://openalex.org/W1589554437","https://openalex.org/W2081580037","https://openalex.org/W2112344871","https://openalex.org/W2113242816","https://openalex.org/W2125055259","https://openalex.org/W2133990480","https://openalex.org/W2136961259","https://openalex.org/W2250243742","https://openalex.org/W2251379416","https://openalex.org/W2252057809","https://openalex.org/W2294703018","https://openalex.org/W2401768650","https://openalex.org/W2467186984","https://openalex.org/W2962750587","https://openalex.org/W4386506836"],"related_works":["https://openalex.org/W2485218895","https://openalex.org/W4245603863","https://openalex.org/W2067332667","https://openalex.org/W3214826749","https://openalex.org/W3151429644","https://openalex.org/W2972573190","https://openalex.org/W4302307487","https://openalex.org/W2035585234","https://openalex.org/W2005894387","https://openalex.org/W2117643817"],"abstract_inverted_index":{"In":[0,52],"this":[1],"paper,":[2],"we":[3],"describe":[4],"the":[5,9,42,48,77],"approach":[6,37,56],"used":[7],"by":[8],"UPF-taln":[10],"team":[11],"for":[12,83,93],"tasks":[13],"10":[14],"and":[15,28,66,86],"11":[16],"of":[17,31],"SemEval":[18],"2015":[19],"that":[20],"respectively":[21],"focused":[22],"on":[23],"\"Sentiment":[24,29],"Analysis":[25,30],"in":[26,34,41],"Twitter\"":[27],"Figurative":[32],"Language":[33],"Twitter\".":[35],"Our":[36],"achieved":[38],"satisfactory":[39],"results":[40],"figurative":[43],"language":[44],"analysis":[45],"task,":[46],"obtaining":[47],"second":[49],"best":[50],"result.":[51],"task":[53,84,94],"10,":[54,85],"our":[55],"obtained":[57],"acceptable":[58],"performances.":[59],"We":[60,71],"experimented":[61],"with":[62,88],"both":[63],"wordbased":[64],"features":[65],"domain-independent":[67],"intrinsic":[68],"word":[69],"features.":[70],"exploited":[72],"two":[73],"machine":[74],"learning":[75],"methods:":[76],"supervised":[78],"algorithm":[79,92],"Support":[80],"Vector":[81],"Machines":[82],"Random-Sub-Space":[87],"M5P":[89],"as":[90],"base":[91],"11.":[95]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2018,"cited_by_count":3},{"year":2016,"cited_by_count":2}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}