{"id":"https://openalex.org/W2472386668","doi":"https://doi.org/10.18653/v1/s16-1077","title":"iLab-Edinburgh at SemEval-2016 Task 7: A Hybrid Approach for Determining Sentiment Intensity of Arabic Twitter Phrases","display_name":"iLab-Edinburgh at SemEval-2016 Task 7: A Hybrid Approach for Determining Sentiment Intensity of Arabic Twitter Phrases","publication_year":2016,"publication_date":"2016-01-01","ids":{"openalex":"https://openalex.org/W2472386668","doi":"https://doi.org/10.18653/v1/s16-1077","mag":"2472386668"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s16-1077","doi":"https://doi.org/10.18653/v1/s16-1077","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-1077","pdf_url":"https://www.aclweb.org/anthology/S16-1077.pdf","source":{"id":"https://openalex.org/S4363608670","display_name":"International Workshop on Semantic Evaluation (SemEval)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 10th International Workshop on Semantic Evaluation (SemEval-2016)","raw_type":"proceedings-article"},"volume":null,"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://www.aclweb.org/anthology/S16-1077.pdf","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5017334210","display_name":"Eshrag Ali Refaee","orcid":"https://orcid.org/0000-0003-2344-0693","observed_orcids":["https://orcid.org/0000-0003-2344-0693"]},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":false,"raw_author_name":"Eshrag Refaee","raw_affiliation_strings":["Interaction Lab, School of Mathematical and Computer Sciences, Heriot-Watt University, EH14 4AS Edinburgh, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Interaction Lab, School of Mathematical and Computer Sciences, Heriot-Watt University, EH14 4AS Edinburgh, United Kingdom","institution_ids":["https://openalex.org/I32062511"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5076593865","display_name":"Verena Rieser","orcid":"https://orcid.org/0000-0001-6117-4395","observed_orcids":["https://orcid.org/0000-0001-6117-4395"]},"institutions":[{"id":"https://openalex.org/I32062511","display_name":"Heriot-Watt University","ror":"https://ror.org/04mghma93","country_code":"GB","type":"education","lineage":["https://openalex.org/I32062511"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Verena Rieser","raw_affiliation_strings":["Interaction Lab, School of Mathematical and Computer Sciences, Heriot-Watt University, EH14 4AS Edinburgh, United Kingdom"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Interaction Lab, School of Mathematical and Computer Sciences, Heriot-Watt University, EH14 4AS Edinburgh, United Kingdom","institution_ids":["https://openalex.org/I32062511"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5076593865"],"corresponding_institution_ids":["https://openalex.org/I32062511"],"apc_list":null,"apc_paid":null,"fwci":3.0529,"has_fulltext":true,"cited_by_count":24,"citation_normalized_percentile":{"value":0.93829241,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":89,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"474","last_page":"480"},"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/T10667","display_name":"Emotion and Mood Recognition","score":0.0,"subfield":{"id":"https://openalex.org/subfields/3205","display_name":"Experimental and Cognitive Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.0,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/sentiment-intensity","display_name":"sentiment intensity","score":0.9509999752044678},{"id":"https://openalex.org/keywords/arabic-sentiment-analysis","display_name":"Arabic sentiment analysis","score":0.8309999704360962},{"id":"https://openalex.org/keywords/twitter","display_name":"Twitter","score":0.7129999995231628}],"concepts":[{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.9002581834793091},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8058844208717346},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7323395013809204},{"id":"https://openalex.org/C96455323","wikidata":"https://www.wikidata.org/wiki/Q13955","display_name":"Arabic","level":2,"score":0.6781134009361267},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6603631973266602},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6236629486083984},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5726539492607117},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.4370807111263275},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.19083824753761292},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.18139034509658813},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.07128176093101501},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/s16-1077","doi":"https://doi.org/10.18653/v1/s16-1077","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-1077","pdf_url":"https://www.aclweb.org/anthology/S16-1077.pdf","source":{"id":"https://openalex.org/S4363608670","display_name":"International Workshop on Semantic Evaluation (SemEval)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 10th International Workshop on Semantic Evaluation (SemEval-2016)","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/s16-1077","doi":"https://doi.org/10.18653/v1/s16-1077","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s16-1077","pdf_url":"https://www.aclweb.org/anthology/S16-1077.pdf","source":{"id":"https://openalex.org/S4363608670","display_name":"International Workshop on Semantic Evaluation (SemEval)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"listed_in":[],"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"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 10th International Workshop on Semantic Evaluation (SemEval-2016)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"sustainable_development_goals_aurora":[{"score":0.5699999928474426,"id":"https://metadata.un.org/sdg/4","display_name":"Quality education"}],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2472386668.pdf","grobid_xml":"https://content.openalex.org/works/W2472386668.grobid-xml"},"referenced_works_count":31,"referenced_works":["https://openalex.org/W38739846","https://openalex.org/W192118262","https://openalex.org/W1570448133","https://openalex.org/W1743243001","https://openalex.org/W1785674045","https://openalex.org/W1987425720","https://openalex.org/W2011342764","https://openalex.org/W2022204871","https://openalex.org/W2022792389","https://openalex.org/W2057854333","https://openalex.org/W2066129432","https://openalex.org/W2084046180","https://openalex.org/W2124752409","https://openalex.org/W2143426320","https://openalex.org/W2145139979","https://openalex.org/W2148263003","https://openalex.org/W2151810470","https://openalex.org/W2157963512","https://openalex.org/W2162357159","https://openalex.org/W2182468807","https://openalex.org/W2250243742","https://openalex.org/W2250427924","https://openalex.org/W2250522473","https://openalex.org/W2250732891","https://openalex.org/W2250816155","https://openalex.org/W2251526503","https://openalex.org/W2252033489","https://openalex.org/W2267835966","https://openalex.org/W2464521204","https://openalex.org/W2725149427","https://openalex.org/W2912934387"],"related_works":["https://openalex.org/W2807683594","https://openalex.org/W2604645204","https://openalex.org/W2470714457","https://openalex.org/W3117023590","https://openalex.org/W2296137540","https://openalex.org/W2750817326","https://openalex.org/W2464521204","https://openalex.org/W2468498295","https://openalex.org/W2494614653","https://openalex.org/W2461533682"],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"the":[3,10,41,63],"iLab-Edinburgh":[4],"Sentiment":[5],"Analysis":[6],"system,":[7],"winner":[8],"of":[9,22,47,72,78,87],"Arabic":[11,38],"Twitter":[12,39],"Task":[13],"7":[14],"in":[15,93],"SemEval-2016.The":[16],"system":[17,83],"employs":[18],"a":[19,30,36,70,76],"hybrid":[20],"approach":[21],"supervised":[23,42],"learning":[24],"and":[25],"rule-based":[26],"methods":[27],"to":[28,52],"predict":[29],"sentiment":[31,81],"intensity":[32],"(SI)":[33],"score":[34,57,66],"for":[35,58],"given":[37,60],"phrase.First,":[40],"method":[43],"uses":[44],"an":[45,54],"ensemble":[46],"trained":[48],"linear":[49],"regression":[50],"models":[51],"produce":[53],"initial":[55],"SI":[56,65],"each":[59],"text":[61],"instance.Second,":[62],"resulting":[64],"is":[67],"adjusted":[68],"using":[69],"set":[71],"rules":[73],"that":[74],"exploit":[75],"number":[77],"publicly":[79],"available":[80],"lexica.The":[82],"demonstrates":[84],"strong":[85],"results":[86],"0.536":[88],"Kendall":[89],"score,":[90],"ranking":[91],"top":[92],"this":[94],"task.":[95]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":3},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":4},{"year":2018,"cited_by_count":3},{"year":2017,"cited_by_count":9},{"year":2016,"cited_by_count":1}],"updated_date":"2026-10-30T12:39:25.321706","created_date":"2016-07-22T00:00:00"}