{"id":"https://openalex.org/W3158581718","doi":"https://doi.org/10.1109/isspit51521.2020.9408866","title":"Sentiment analysis using an ensemble approach of BiGRU model: A case study of AMIS tweets","display_name":"Sentiment analysis using an ensemble approach of BiGRU model: A case study of AMIS tweets","publication_year":2020,"publication_date":"2020-12-09","ids":{"openalex":"https://openalex.org/W3158581718","doi":"https://doi.org/10.1109/isspit51521.2020.9408866","mag":"3158581718"},"language":"en","primary_location":{"id":"doi:10.1109/isspit51521.2020.9408866","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspit51521.2020.9408866","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","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/A5059235837","display_name":"Zabit Hameed","orcid":"https://orcid.org/0000-0003-2514-1064"},"institutions":[{"id":"https://openalex.org/I136040515","display_name":"Universidad de Deusto","ror":"https://ror.org/00ne6sr39","country_code":"ES","type":"education","lineage":["https://openalex.org/I136040515"]}],"countries":["ES"],"is_corresponding":true,"raw_author_name":"Zabit Hameed","raw_affiliation_strings":["University of Deusto, Bilbao, Spain"],"affiliations":[{"raw_affiliation_string":"University of Deusto, Bilbao, Spain","institution_ids":["https://openalex.org/I136040515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5102904512","display_name":"Serhii Shapoval","orcid":"https://orcid.org/0000-0002-3531-9316"},"institutions":[{"id":"https://openalex.org/I136040515","display_name":"Universidad de Deusto","ror":"https://ror.org/00ne6sr39","country_code":"ES","type":"education","lineage":["https://openalex.org/I136040515"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Serhii Shapoval","raw_affiliation_strings":["University of Deusto, Bilbao, Spain"],"affiliations":[{"raw_affiliation_string":"University of Deusto, Bilbao, Spain","institution_ids":["https://openalex.org/I136040515"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028149208","display_name":"Begonya Garc\u00eda-Zapirain","orcid":"https://orcid.org/0000-0002-9356-1186"},"institutions":[{"id":"https://openalex.org/I136040515","display_name":"Universidad de Deusto","ror":"https://ror.org/00ne6sr39","country_code":"ES","type":"education","lineage":["https://openalex.org/I136040515"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Begonya Garcia-Zapirain","raw_affiliation_strings":["University of Deusto, Bilbao, Spain"],"affiliations":[{"raw_affiliation_string":"University of Deusto, Bilbao, Spain","institution_ids":["https://openalex.org/I136040515"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005791763","display_name":"Amaia M\u00e9ndez Zorrilla","orcid":"https://orcid.org/0000-0002-0539-4753"},"institutions":[{"id":"https://openalex.org/I136040515","display_name":"Universidad de Deusto","ror":"https://ror.org/00ne6sr39","country_code":"ES","type":"education","lineage":["https://openalex.org/I136040515"]}],"countries":["ES"],"is_corresponding":false,"raw_author_name":"Amaia Mendez Zorilla","raw_affiliation_strings":["University of Deusto, Bilbao, Spain"],"affiliations":[{"raw_affiliation_string":"University of Deusto, Bilbao, Spain","institution_ids":["https://openalex.org/I136040515"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5059235837"],"corresponding_institution_ids":["https://openalex.org/I136040515"],"apc_list":null,"apc_paid":null,"fwci":0.5302,"has_fulltext":false,"cited_by_count":7,"citation_normalized_percentile":{"value":0.74335955,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"5"},"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":0.9997000098228455,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9962000250816345,"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/ensemble-learning","display_name":"Ensemble learning","score":0.6911358833312988},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6666581034660339},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6604883074760437},{"id":"https://openalex.org/keywords/ensemble-forecasting","display_name":"Ensemble forecasting","score":0.6305720806121826},{"id":"https://openalex.org/keywords/measure","display_name":"Measure (data warehouse)","score":0.5984237790107727},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.46689924597740173},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.3951166272163391},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.32834771275520325},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.2749629616737366}],"concepts":[{"id":"https://openalex.org/C45942800","wikidata":"https://www.wikidata.org/wiki/Q245652","display_name":"Ensemble learning","level":2,"score":0.6911358833312988},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6666581034660339},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6604883074760437},{"id":"https://openalex.org/C119898033","wikidata":"https://www.wikidata.org/wiki/Q3433888","display_name":"Ensemble forecasting","level":2,"score":0.6305720806121826},{"id":"https://openalex.org/C2780009758","wikidata":"https://www.wikidata.org/wiki/Q6804172","display_name":"Measure (data warehouse)","level":2,"score":0.5984237790107727},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.46689924597740173},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.3951166272163391},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.32834771275520325},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.2749629616737366}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/isspit51521.2020.9408866","is_oa":false,"landing_page_url":"https://doi.org/10.1109/isspit51521.2020.9408866","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2020 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W1832693441","https://openalex.org/W2064675550","https://openalex.org/W2084046180","https://openalex.org/W2153579005","https://openalex.org/W2157331557","https://openalex.org/W2166706824","https://openalex.org/W2250539671","https://openalex.org/W2251124635","https://openalex.org/W2306706380","https://openalex.org/W2562607067","https://openalex.org/W2606089314","https://openalex.org/W2801716390","https://openalex.org/W2803871820","https://openalex.org/W2886787252","https://openalex.org/W2901078833","https://openalex.org/W2923528470","https://openalex.org/W2947851192","https://openalex.org/W2964236337","https://openalex.org/W3008721660","https://openalex.org/W3016921356","https://openalex.org/W3080168576","https://openalex.org/W4210984920","https://openalex.org/W4294170691","https://openalex.org/W6682691769","https://openalex.org/W6751475230","https://openalex.org/W6753344729"],"related_works":["https://openalex.org/W4376643315","https://openalex.org/W4324137541","https://openalex.org/W2794896638","https://openalex.org/W2900445707","https://openalex.org/W2891633941","https://openalex.org/W4285741730","https://openalex.org/W1191482210","https://openalex.org/W4285046548","https://openalex.org/W3202800081","https://openalex.org/W4210302090"],"abstract_inverted_index":{"This":[0],"paper":[1],"presents":[2],"a":[3,31,98],"comparably":[4],"simpler":[5],"yet":[6],"effective":[7],"deep":[8],"learning":[9],"approach":[10,42,92],"for":[11,43],"sentiment":[12],"analysis":[13],"of":[14,47,56,64,74,80,87],"Twitter":[15],"topics.":[16],"We":[17,34],"automatically":[18],"collected":[19],"positive":[20],"and":[21,24,28],"negative":[22],"tweets":[23],"labeled":[25],"them":[26],"manually,":[27],"thus":[29],"created":[30],"new":[32],"dataset.":[33],"then":[35],"leveraged":[36],"BiGRU":[37,51],"model":[38,52],"with":[39,83],"an":[40,54,61,71],"ensemble":[41,68,91],"the":[44,67,78,84,90],"binary":[45],"classification":[46],"tweets.":[48],"Our":[49],"finalized":[50],"offered":[53,93],"accuracy":[55,79],"84.8%":[57],"as":[58,60],"well":[59],"averaged":[62,72,85],"F1-measure":[63,86],"84.8%(\u00b10.3).":[65],"Moreover,":[66],"approach,":[69],"using":[70],"prediction":[73],"5-fold":[75],"strategy,":[76],"provided":[77],"86.3%":[81],"along":[82],"86.3%(\u00b10.05).":[88],"Consequently,":[89],"better":[94],"performance":[95],"even":[96],"on":[97],"smaller":[99],"dataset":[100],"used":[101],"in":[102],"this":[103],"study.":[104]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":3},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
