{"id":"https://openalex.org/W2610665768","doi":"https://doi.org/10.18653/v1/s17-2108","title":"Amobee at SemEval-2017 Task 4: Deep Learning System for Sentiment Detection on Twitter","display_name":"Amobee at SemEval-2017 Task 4: Deep Learning System for Sentiment Detection on Twitter","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2610665768","doi":"https://doi.org/10.18653/v1/s17-2108","mag":"2610665768"},"language":"en","primary_location":{"id":"doi:10.18653/v1/s17-2108","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s17-2108","pdf_url":"https://www.aclweb.org/anthology/S17-2108.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 11th International Workshop on Semantic Evaluation\n          (SemEval-2017)","raw_type":"proceedings-article"},"type":"article","indexed_in":["arxiv","crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/S17-2108.pdf","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Alon Rozental","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Alon Rozental","raw_affiliation_strings":["Amobee, Tel Aviv, Israel"],"affiliations":[{"raw_affiliation_string":"Amobee, Tel Aviv, Israel","institution_ids":[]}]},{"author_position":"last","author":{"id":null,"display_name":"Daniel Fleischer","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Daniel Fleischer","raw_affiliation_strings":["Amobee, Tel Aviv, Israel"],"affiliations":[{"raw_affiliation_string":"Amobee, Tel Aviv, Israel","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.4154,"has_fulltext":true,"cited_by_count":4,"citation_normalized_percentile":{"value":0.70832499,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"653","last_page":"658"},"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/T10028","display_name":"Topic Modeling","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/T10181","display_name":"Natural Language Processing Techniques","score":0.9988999962806702,"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/task","display_name":"Task (project management)","score":0.7544000148773193},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.6227999925613403},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.5827000141143799},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.5680000185966492},{"id":"https://openalex.org/keywords/semeval","display_name":"SemEval","score":0.48989999294281006},{"id":"https://openalex.org/keywords/logistic-regression","display_name":"Logistic regression","score":0.4018999934196472},{"id":"https://openalex.org/keywords/supervised-learning","display_name":"Supervised learning","score":0.37380000948905945}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7924000024795532},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.777999997138977},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.7544000148773193},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.6227999925613403},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.5827000141143799},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.5680000185966492},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.5450999736785889},{"id":"https://openalex.org/C44572571","wikidata":"https://www.wikidata.org/wiki/Q7448970","display_name":"SemEval","level":3,"score":0.48989999294281006},{"id":"https://openalex.org/C151956035","wikidata":"https://www.wikidata.org/wiki/Q1132755","display_name":"Logistic regression","level":2,"score":0.4018999934196472},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3993000090122223},{"id":"https://openalex.org/C136389625","wikidata":"https://www.wikidata.org/wiki/Q334384","display_name":"Supervised learning","level":3,"score":0.37380000948905945},{"id":"https://openalex.org/C207201462","wikidata":"https://www.wikidata.org/wiki/Q182505","display_name":"Bayes' theorem","level":3,"score":0.3562000095844269},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.34220001101493835},{"id":"https://openalex.org/C51632099","wikidata":"https://www.wikidata.org/wiki/Q3985153","display_name":"Training set","level":2,"score":0.31130000948905945},{"id":"https://openalex.org/C47702885","wikidata":"https://www.wikidata.org/wiki/Q5441227","display_name":"Feedforward neural network","level":3,"score":0.29750001430511475},{"id":"https://openalex.org/C175154964","wikidata":"https://www.wikidata.org/wiki/Q380077","display_name":"Task analysis","level":3,"score":0.2921000123023987},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.2754000127315521},{"id":"https://openalex.org/C2984842247","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep neural networks","level":3,"score":0.262800008058548},{"id":"https://openalex.org/C83546350","wikidata":"https://www.wikidata.org/wiki/Q1139051","display_name":"Regression","level":2,"score":0.25780001282691956}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.18653/v1/s17-2108","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s17-2108","pdf_url":"https://www.aclweb.org/anthology/S17-2108.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 11th International Workshop on Semantic Evaluation\n          (SemEval-2017)","raw_type":"proceedings-article"},{"id":"pmh:oai:arXiv.org:1705.01306","is_oa":true,"landing_page_url":"http://arxiv.org/abs/1705.01306","pdf_url":"https://arxiv.org/pdf/1705.01306","source":{"id":"https://openalex.org/S4306400194","display_name":"arXiv (Cornell University)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I205783295","host_organization_name":"Cornell University","host_organization_lineage":["https://openalex.org/I205783295"],"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":"text"}],"best_oa_location":{"id":"doi:10.18653/v1/s17-2108","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/s17-2108","pdf_url":"https://www.aclweb.org/anthology/S17-2108.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 11th International Workshop on Semantic Evaluation\n          (SemEval-2017)","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2610665768.pdf","grobid_xml":"https://content.openalex.org/works/W2610665768.grobid-xml"},"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"This":[0],"paper":[1],"describes":[2],"the":[3,35,50,56,60],"Amobee":[4],"sentiment":[5,32],"analysis":[6],"system,":[7],"adapted":[8],"to":[9,46],"compete":[10],"in":[11],"SemEval":[12],"2017":[13],"task":[14,63],"4.":[15],"The":[16,53],"system":[17],"consists":[18],"of":[19,25,37],"two":[20],"parts:":[21],"a":[22,30],"supervised":[23],"training":[24],"RNN":[26],"models":[27],"based":[28],"on":[29,59],"Twitter":[31],"treebank,":[33],"and":[34,42],"use":[36],"feedforward":[38],"NN,":[39],"Naive":[40],"Bayes":[41],"logistic":[43],"regression":[44],"classifiers":[45],"produce":[47],"predictions":[48],"for":[49],"different":[51],"sub-tasks.":[52],"algorithm":[54],"reached":[55],"3rd":[57],"place":[58],"5-label":[61],"classification":[62],"(sub-task":[64],"C).":[65]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":1},{"year":2019,"cited_by_count":1}],"updated_date":"2026-03-20T23:20:44.827607","created_date":"2017-05-12T00:00:00"}
