{"id":"https://openalex.org/W4388821286","doi":"https://doi.org/10.1109/idsta58916.2023.10317863","title":"The Role of Emojis in Sentiment Analysis of Financial Microblogs","display_name":"The Role of Emojis in Sentiment Analysis of Financial Microblogs","publication_year":2023,"publication_date":"2023-10-24","ids":{"openalex":"https://openalex.org/W4388821286","doi":"https://doi.org/10.1109/idsta58916.2023.10317863"},"language":"en","primary_location":{"id":"doi:10.1109/idsta58916.2023.10317863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/idsta58916.2023.10317863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Fourth International Conference on Intelligent Data Science Technologies and Applications (IDSTA)","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/A5102858942","display_name":"Ahmed Mahrous","orcid":"https://orcid.org/0000-0003-4694-5336"},"institutions":[{"id":"https://openalex.org/I60342839","display_name":"Qatar University","ror":"https://ror.org/00yhnba62","country_code":"QA","type":"education","lineage":["https://openalex.org/I60342839"]}],"countries":["QA"],"is_corresponding":true,"raw_author_name":"Ahmed Mahrous","raw_affiliation_strings":["College of Finance and Economics, Qatar University,Doha,Qatar","College of Finance and Economics, Qatar University, Doha, Qatar"],"affiliations":[{"raw_affiliation_string":"College of Finance and Economics, Qatar University,Doha,Qatar","institution_ids":["https://openalex.org/I60342839"]},{"raw_affiliation_string":"College of Finance and Economics, Qatar University, Doha, Qatar","institution_ids":["https://openalex.org/I60342839"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030066648","display_name":"Jens Schneider","orcid":"https://orcid.org/0000-0002-0546-2816"},"institutions":[{"id":"https://openalex.org/I92528248","display_name":"Qatar Foundation","ror":"https://ror.org/01cawbq05","country_code":"QA","type":"funder","lineage":["https://openalex.org/I92528248"]},{"id":"https://openalex.org/I4210144839","display_name":"Hamad bin Khalifa University","ror":"https://ror.org/03eyq4y97","country_code":"QA","type":"education","lineage":["https://openalex.org/I4210144839"]}],"countries":["QA"],"is_corresponding":false,"raw_author_name":"Jens Schneider","raw_affiliation_strings":["College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation,Doha,Qatar","College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar"],"affiliations":[{"raw_affiliation_string":"College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation,Doha,Qatar","institution_ids":["https://openalex.org/I4210144839","https://openalex.org/I92528248"]},{"raw_affiliation_string":"College of Science and Engineering, Hamad Bin Khalifa University, Qatar Foundation, Doha, Qatar","institution_ids":["https://openalex.org/I4210144839","https://openalex.org/I92528248"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5065932621","display_name":"Roberto Di Pietro","orcid":"https://orcid.org/0000-0003-1909-0336"},"institutions":[{"id":"https://openalex.org/I71920554","display_name":"King Abdullah University of Science and Technology","ror":"https://ror.org/01q3tbs38","country_code":"SA","type":"education","lineage":["https://openalex.org/I71920554"]}],"countries":["SA"],"is_corresponding":false,"raw_author_name":"Roberto Di Pietro","raw_affiliation_strings":["KAUST,RC3, CEMSE Division,Thuwal,Saudi Arabia","RC3, CEMSE Division, KAUST, Thuwal, Saudi Arabia"],"affiliations":[{"raw_affiliation_string":"KAUST,RC3, CEMSE Division,Thuwal,Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]},{"raw_affiliation_string":"RC3, CEMSE Division, KAUST, Thuwal, Saudi Arabia","institution_ids":["https://openalex.org/I71920554"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5102858942"],"corresponding_institution_ids":["https://openalex.org/I60342839"],"apc_list":null,"apc_paid":null,"fwci":0.3657,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.61198129,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":95},"biblio":{"volume":null,"issue":null,"first_page":"76","last_page":"84"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13155","display_name":"Digital Communication and Language","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T13155","display_name":"Digital Communication and Language","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/1709","display_name":"Human-Computer Interaction"},"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","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"}},{"id":"https://openalex.org/T10609","display_name":"Digital Marketing and Social Media","score":0.9663000106811523,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/microblogging","display_name":"Microblogging","score":0.863213062286377},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.8004809617996216},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.704223096370697},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6674362421035767},{"id":"https://openalex.org/keywords/emoji","display_name":"Emoji","score":0.6469099521636963},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5639873147010803},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5010354518890381},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47122204303741455},{"id":"https://openalex.org/keywords/set","display_name":"Set (abstract data type)","score":0.4110291600227356},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.38807323575019836},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.35155758261680603},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.26159167289733887}],"concepts":[{"id":"https://openalex.org/C143275388","wikidata":"https://www.wikidata.org/wiki/Q92438","display_name":"Microblogging","level":3,"score":0.863213062286377},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.8004809617996216},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.704223096370697},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6674362421035767},{"id":"https://openalex.org/C2779247141","wikidata":"https://www.wikidata.org/wiki/Q1049294","display_name":"Emoji","level":3,"score":0.6469099521636963},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5639873147010803},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5010354518890381},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47122204303741455},{"id":"https://openalex.org/C177264268","wikidata":"https://www.wikidata.org/wiki/Q1514741","display_name":"Set (abstract data type)","level":2,"score":0.4110291600227356},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.38807323575019836},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.35155758261680603},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.26159167289733887},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/idsta58916.2023.10317863","is_oa":false,"landing_page_url":"https://doi.org/10.1109/idsta58916.2023.10317863","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 Fourth International Conference on Intelligent Data Science Technologies and Applications (IDSTA)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.4099999964237213,"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4"}],"awards":[{"id":"https://openalex.org/G7674813164","display_name":null,"funder_award_id":"8-L-2-0517-21039","funder_id":"https://openalex.org/F4320332753","funder_display_name":"Qatar National Research Fund"}],"funders":[{"id":"https://openalex.org/F4320332753","display_name":"Qatar National Research Fund","ror":"https://ror.org/01svaqq28"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":54,"referenced_works":["https://openalex.org/W1584017212","https://openalex.org/W1597136917","https://openalex.org/W2068451972","https://openalex.org/W2119595472","https://openalex.org/W2121968240","https://openalex.org/W2122522916","https://openalex.org/W2131774270","https://openalex.org/W2134519938","https://openalex.org/W2139511937","https://openalex.org/W2471221792","https://openalex.org/W2587108171","https://openalex.org/W2734498027","https://openalex.org/W2744280729","https://openalex.org/W2766332866","https://openalex.org/W2788440980","https://openalex.org/W2793625747","https://openalex.org/W2795084954","https://openalex.org/W2801661935","https://openalex.org/W2807374657","https://openalex.org/W2808770849","https://openalex.org/W2840746492","https://openalex.org/W2883853499","https://openalex.org/W2889762799","https://openalex.org/W2892468315","https://openalex.org/W2894059694","https://openalex.org/W2904013400","https://openalex.org/W2910064757","https://openalex.org/W2933029306","https://openalex.org/W2945387691","https://openalex.org/W2962416811","https://openalex.org/W2974836096","https://openalex.org/W2980428304","https://openalex.org/W2995797250","https://openalex.org/W3032928500","https://openalex.org/W3036114413","https://openalex.org/W3044866491","https://openalex.org/W3093232402","https://openalex.org/W3102853424","https://openalex.org/W3121285187","https://openalex.org/W3122069311","https://openalex.org/W3124986135","https://openalex.org/W3152524748","https://openalex.org/W3173999034","https://openalex.org/W3207397762","https://openalex.org/W4205807230","https://openalex.org/W4285796399","https://openalex.org/W4288333953","https://openalex.org/W4318751726","https://openalex.org/W4365799947","https://openalex.org/W4385572847","https://openalex.org/W6697052316","https://openalex.org/W6785785058","https://openalex.org/W6840756468","https://openalex.org/W6850009913"],"related_works":["https://openalex.org/W2997778406","https://openalex.org/W2728430307","https://openalex.org/W2107786128","https://openalex.org/W2053241453","https://openalex.org/W2153980712","https://openalex.org/W2537388533","https://openalex.org/W2978974359","https://openalex.org/W2036556872","https://openalex.org/W2021183651","https://openalex.org/W2017590198"],"abstract_inverted_index":{"The":[0,224],"application":[1],"of":[2,25,42,66,120,125],"sentiment":[3,123,170],"analysis":[4,32,124,171],"to":[5,17,27,48,68,92,116,139,165,177,197,208],"the":[6,37,56,64,80,87,118,163,210,236,242],"financial":[7,126,222],"sector":[8],"is":[9,72,82,85,184,188,206],"a":[10,23,178,198],"field":[11],"that":[12,39,89],"has":[13,21],"been":[14],"revamped":[15],"thanks":[16],"social":[18,60,129],"media,":[19],"which":[20],"unleashed":[22],"trove":[24],"data":[26,43,141,205],"analyze.":[28],"In":[29,62,97],"particular,":[30,63,98],"text":[31],"techniques":[33],"have":[34,46],"benefited":[35],"from":[36,106],"attention":[38],"large":[40],"part":[41],"science":[44],"researchers":[45],"devoted":[47],"it.":[49],"However,":[50],"as":[51],"demographics":[52],"evolve,":[53],"so":[54],"do":[55],"communication":[57],"forms":[58],"on":[59,79,128,174,231],"media.":[61,130],"usage":[65,220],"emojis":[67,121],"carry":[69],"whole":[70],"concepts":[71],"more":[73,75,101],"and":[74,137,147,153],"diffused,":[76],"though":[77],"research":[78,240],"topic":[81],"lacking.":[83],"That":[84],"exactly":[86],"gap":[88],"we":[90,108,161,213],"intend":[91],"cover":[93],"with":[94],"this":[95],"contribution.":[96],"after":[99],"collecting":[100],"than":[102,228],"18.5":[103],"million":[104],"posts":[105,127],"StockTwits,":[107],"use":[109],"different":[110],"supervised":[111],"learning":[112],"models":[113,172],"in":[114,122,221,241],"order":[115],"determine":[117],"role":[119],"We":[131],"assess":[132],"model":[133],"accuracy,":[134],"training/prediction":[135],"speed,":[136],"sensitivity":[138],"training":[140,169,187],"set":[142],"size":[143],"for":[144,238],"both":[145],"emojis-only":[146],"text-only":[148,179],"data,":[149],"using":[150],"logistic":[151],"regression":[152],"BiLSTM":[154],"models.":[155],"Our":[156],"main":[157],"findings":[158],"are":[159,162,195],"staggering;":[160],"first":[164],"show":[166,214],"that,":[167],"when":[168],"exclusively":[173],"emojis,":[175],"compared":[176],"approach:":[180],"(i)":[181],"achieved":[182],"accuracy":[183],"competitive;":[185],"(ii)":[186],"32":[189],"times":[190,194,203],"faster;":[191],"(iii)":[192],"prediction":[193],"reduced":[196],"third;":[199],"and,":[200],"(iv)":[201],"40":[202],"less":[204],"needed":[207],"train":[209],"model.":[211],"Additionally,":[212],"some":[215],"interesting":[216,230],"patterns":[217],"regarding":[218],"emoji":[219],"microblogs.":[223],"cited":[225],"contributions,":[226],"other":[227],"being":[229],"their":[232],"own,":[233],"also":[234],"pave":[235],"way":[237],"further":[239],"field.":[243]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}