{"id":"https://openalex.org/W4312553314","doi":"https://doi.org/10.1109/iicaiet55139.2022.9936756","title":"Stock Market Price Prediction: Text Analytics of the GameStop Short Squeeze","display_name":"Stock Market Price Prediction: Text Analytics of the GameStop Short Squeeze","publication_year":2022,"publication_date":"2022-09-13","ids":{"openalex":"https://openalex.org/W4312553314","doi":"https://doi.org/10.1109/iicaiet55139.2022.9936756"},"language":"en","primary_location":{"id":"doi:10.1109/iicaiet55139.2022.9936756","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iicaiet55139.2022.9936756","pdf_url":null,"source":{"id":"https://openalex.org/S4363608273","display_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","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/A5059735818","display_name":"Ng Wei Xiang","orcid":null},"institutions":[{"id":"https://openalex.org/I84339108","display_name":"Sunway University","ror":"https://ror.org/04mjt7f73","country_code":"MY","type":"education","lineage":["https://openalex.org/I84339108"]}],"countries":["MY"],"is_corresponding":true,"raw_author_name":"Ng Wei Xiang","raw_affiliation_strings":["School of Engineering and Technology, Sunway University,Petaling Jaya,Malaysia","School of Engineering and Technology, Sunway University, Petaling Jaya, Malaysia"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Technology, Sunway University,Petaling Jaya,Malaysia","institution_ids":["https://openalex.org/I84339108"]},{"raw_affiliation_string":"School of Engineering and Technology, Sunway University, Petaling Jaya, Malaysia","institution_ids":["https://openalex.org/I84339108"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5085980737","display_name":"Mohammad Dabbagh","orcid":"https://orcid.org/0000-0003-2041-0317"},"institutions":[{"id":"https://openalex.org/I84339108","display_name":"Sunway University","ror":"https://ror.org/04mjt7f73","country_code":"MY","type":"education","lineage":["https://openalex.org/I84339108"]}],"countries":["MY"],"is_corresponding":false,"raw_author_name":"Mohammad Dabbagh","raw_affiliation_strings":["School of Engineering and Technology, Sunway University,Petaling Jaya,Malaysia","School of Engineering and Technology, Sunway University, Petaling Jaya, Malaysia"],"affiliations":[{"raw_affiliation_string":"School of Engineering and Technology, Sunway University,Petaling Jaya,Malaysia","institution_ids":["https://openalex.org/I84339108"]},{"raw_affiliation_string":"School of Engineering and Technology, Sunway University, Petaling Jaya, Malaysia","institution_ids":["https://openalex.org/I84339108"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5059735818"],"corresponding_institution_ids":["https://openalex.org/I84339108"],"apc_list":null,"apc_paid":null,"fwci":1.0293,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.75147295,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":96},"biblio":{"volume":null,"issue":null,"first_page":"1","last_page":"6"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9965999722480774,"subfield":{"id":"https://openalex.org/subfields/1803","display_name":"Management Science and Operations Research"},"field":{"id":"https://openalex.org/fields/18","display_name":"Decision Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9873999953269958,"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/T10270","display_name":"Blockchain Technology Applications and Security","score":0.9753000140190125,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/analytics","display_name":"Analytics","score":0.677725076675415},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.6112890243530273},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.5349437594413757},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.4996933937072754},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.49293947219848633},{"id":"https://openalex.org/keywords/social-media-analytics","display_name":"Social media analytics","score":0.4675658345222473},{"id":"https://openalex.org/keywords/scope","display_name":"Scope (computer science)","score":0.4427741467952728},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.4408803880214691},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.41332268714904785},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.38471776247024536},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.3489607572555542},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.23672762513160706},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.21377363801002502},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.18955975770950317},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.1176932156085968},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.09740906953811646}],"concepts":[{"id":"https://openalex.org/C79158427","wikidata":"https://www.wikidata.org/wiki/Q485396","display_name":"Analytics","level":2,"score":0.677725076675415},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.6112890243530273},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.5349437594413757},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.4996933937072754},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.49293947219848633},{"id":"https://openalex.org/C2778729106","wikidata":"https://www.wikidata.org/wiki/Q1140126","display_name":"Social media analytics","level":3,"score":0.4675658345222473},{"id":"https://openalex.org/C2778012447","wikidata":"https://www.wikidata.org/wiki/Q1034415","display_name":"Scope (computer science)","level":2,"score":0.4427741467952728},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.4408803880214691},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.41332268714904785},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.38471776247024536},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.3489607572555542},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.23672762513160706},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.21377363801002502},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.18955975770950317},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.1176932156085968},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.09740906953811646},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.0},{"id":"https://openalex.org/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"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/iicaiet55139.2022.9936756","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iicaiet55139.2022.9936756","pdf_url":null,"source":{"id":"https://openalex.org/S4363608273","display_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"conference"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2022 IEEE International Conference on Artificial Intelligence in Engineering and Technology (IICAIET)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Good health and well-being","id":"https://metadata.un.org/sdg/3","score":0.5699999928474426}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":14,"referenced_works":["https://openalex.org/W2047443164","https://openalex.org/W2138156863","https://openalex.org/W2162599512","https://openalex.org/W2542080616","https://openalex.org/W2963756544","https://openalex.org/W3043424630","https://openalex.org/W3145531040","https://openalex.org/W3158915430","https://openalex.org/W3185923516","https://openalex.org/W3214208027","https://openalex.org/W4240050248","https://openalex.org/W4243532745","https://openalex.org/W4250584464","https://openalex.org/W6922597575"],"related_works":["https://openalex.org/W1440043730","https://openalex.org/W2752017774","https://openalex.org/W2252197266","https://openalex.org/W2309196980","https://openalex.org/W4232432449","https://openalex.org/W3095817971","https://openalex.org/W4386456676","https://openalex.org/W4200138770","https://openalex.org/W3010943912","https://openalex.org/W2948425927"],"abstract_inverted_index":{"Analytics":[0],"on":[1,63,108,165],"the":[2,28,32,36,73,82,109,118,127,146,150,159,166,181,186,189,194],"stock":[3],"market":[4],"is":[5],"always":[6],"a":[7,48,94,100,141,154],"topic":[8],"of":[9,39,50,103,121,129,149,161,168,185,196],"interest":[10],"by":[11,53,59,89],"many":[12],"including":[13],"researchers":[14],"to":[15,144,157,179],"prove":[16],"that":[17,99,116],"financial":[18],"outcomes":[19],"could":[20],"be":[21,177],"analyzed":[22],"beforehand":[23],"therefore":[24],"producing":[25],"insights.":[26],"In":[27,124],"year":[29],"2020":[30],"where":[31,137],"pandemic":[33],"hit":[34],"globally,":[35],"share":[37,162,197],"price":[38,163,198],"GameStop":[40],"suffered":[41],"an":[42],"unprecedented":[43],"short":[44,74],"squeeze":[45,75],"which":[46],"was":[47,67,84,97,131],"result":[49],"selling":[51],"activities":[52,58],"major":[54],"investors":[55],"and":[56,78,87,115,152,183],"buying":[57],"netizens":[60],"primarily":[61],"active":[62],"Reddit.":[64],"Online":[65],"media":[66],"actively":[68],"covering":[69],"surface":[70],"stories":[71],"about":[72,81],"but":[76,191],"detailed":[77],"extensive":[79],"research":[80,95,104],"event":[83,110],"not":[85,175],"seen":[86],"done":[88],"many.":[90],"Upon":[91],"further":[92],"investigation,":[93],"gap":[96],"found":[98],"limited":[101],"scale":[102],"had":[105],"performed":[106],"analysis":[107],"with":[111],"text":[112,147],"analytics":[113,130],"approach":[114],"formulates":[117],"larger":[119],"goal":[120],"this":[122,125],"research.":[123],"paper,":[126],"scope":[128],"mainly":[132],"split":[133],"into":[134],"two":[135],"approaches,":[136],"we":[138,173],"first":[139],"build":[140],"clustering":[142],"model":[143,156],"understand":[145],"behavior":[148],"community,":[151],"then":[153],"regression":[155],"predict":[158],"changes":[160],"based":[164],"features":[167],"their":[169],"text.":[170],"With":[171],"that,":[172],"will":[174],"only":[176],"able":[178],"discover":[180],"behaviors":[182],"sentiment":[184],"community":[187],"towards":[188],"stock,":[190],"also":[192],"predicting":[193],"movement":[195],"using":[199],"textual":[200],"data.":[201]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
