{"id":"https://openalex.org/W3163561468","doi":"https://doi.org/10.1145/3452940.3452954","title":"Stock Movement Classification from Twitter via Mogrifier Based Memory Cells with Attention Mechanism","display_name":"Stock Movement Classification from Twitter via Mogrifier Based Memory Cells with Attention Mechanism","publication_year":2020,"publication_date":"2020-12-03","ids":{"openalex":"https://openalex.org/W3163561468","doi":"https://doi.org/10.1145/3452940.3452954","mag":"3163561468"},"language":"en","primary_location":{"id":"doi:10.1145/3452940.3452954","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3452940.3452954","pdf_url":null,"source":{"id":"https://openalex.org/S4306523813","display_name":"Proceedings of the 3rd International Conference on Information Technologies and Electrical Engineering","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":"Proceedings of the 3rd International Conference on Information Technologies and Electrical Engineering","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103262975","display_name":"Tian Qin","orcid":"https://orcid.org/0000-0002-3466-6041"},"institutions":[{"id":"https://openalex.org/I157725225","display_name":"University of Illinois Urbana-Champaign","ror":"https://ror.org/047426m28","country_code":"US","type":"education","lineage":["https://openalex.org/I157725225"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Tian Qin","raw_affiliation_strings":["Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, IL, US"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Department of Statistics, University of Illinois at Urbana-Champaign, Champaign, IL, US","institution_ids":["https://openalex.org/I157725225"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5103262975"],"corresponding_institution_ids":["https://openalex.org/I157725225"],"apc_list":null,"apc_paid":null,"fwci":0.2924,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.58663502,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"74","last_page":"80"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11326","display_name":"Stock Market Forecasting Methods","score":0.9997000098228455,"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":0.9997000098228455,"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/T11270","display_name":"Complex Systems and Time Series Analysis","score":0.9940000176429749,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T12611","display_name":"Neural Networks and Reservoir Computing","score":0.9891999959945679,"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/computer-science","display_name":"Computer science","score":0.7683027982711792},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.6463329195976257},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.6213614344596863},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5487924814224243},{"id":"https://openalex.org/keywords/volatility","display_name":"Volatility (finance)","score":0.5153636336326599},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.5115143060684204},{"id":"https://openalex.org/keywords/financial-market","display_name":"Financial market","score":0.5039450526237488},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.4960251748561859},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4925437867641449},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.46347033977508545},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.44793617725372314},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.41405177116394043},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.10506659746170044},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.09813317656517029}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7683027982711792},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.6463329195976257},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.6213614344596863},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5487924814224243},{"id":"https://openalex.org/C91602232","wikidata":"https://www.wikidata.org/wiki/Q756115","display_name":"Volatility (finance)","level":2,"score":0.5153636336326599},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.5115143060684204},{"id":"https://openalex.org/C19244329","wikidata":"https://www.wikidata.org/wiki/Q208697","display_name":"Financial market","level":2,"score":0.5039450526237488},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.4960251748561859},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4925437867641449},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.46347033977508545},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.44793617725372314},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.41405177116394043},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.10506659746170044},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.09813317656517029},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3452940.3452954","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3452940.3452954","pdf_url":null,"source":{"id":"https://openalex.org/S4306523813","display_name":"Proceedings of the 3rd International Conference on Information Technologies and Electrical Engineering","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":"Proceedings of the 3rd International Conference on Information Technologies and Electrical Engineering","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":18,"referenced_works":["https://openalex.org/W2001166834","https://openalex.org/W2024760831","https://openalex.org/W2034098634","https://openalex.org/W2093131651","https://openalex.org/W2138628945","https://openalex.org/W2250539671","https://openalex.org/W2469894155","https://openalex.org/W2766736793","https://openalex.org/W2774513877","https://openalex.org/W2774559076","https://openalex.org/W2798058877","https://openalex.org/W2798413829","https://openalex.org/W2833425706","https://openalex.org/W2890096158","https://openalex.org/W2917928566","https://openalex.org/W4231546411","https://openalex.org/W6638824847","https://openalex.org/W6666761814"],"related_works":["https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W1847088711","https://openalex.org/W4225394202","https://openalex.org/W3036642985","https://openalex.org/W3032952384","https://openalex.org/W2964335273","https://openalex.org/W2982145560","https://openalex.org/W2081900870","https://openalex.org/W2645942849"],"abstract_inverted_index":{"A":[0],"growing":[1],"number":[2],"of":[3],"financial":[4],"market":[5,16,110,124],"participants":[6],"use":[7],"the":[8,14,20,49,81,84,89,100,113,119],"deep":[9],"learning":[10,95],"models":[11],"to":[12,62],"predict":[13],"future":[15],"movement":[17],"via":[18],"exploiting":[19],"news":[21],"and":[22,33,53,88],"social":[23],"media":[24],"messages.":[25],"Memory":[26],"cells":[27],"like":[28],"long":[29],"short-term":[30],"memory":[31],"(LSTM)":[32],"gated":[34],"recurrent":[35],"unit":[36],"(GRU),":[37],"though":[38],"play":[39],"indispensable":[40],"roles":[41],"in":[42,71],"sequence":[43],"prediction,":[44],"are":[45],"criticized":[46],"for":[47],"lacking":[48],"interaction":[50],"between":[51,83],"inputs":[52],"previous":[54,85],"context.":[55],"The":[56,77],"Mogrifier":[57,114],"LSTM":[58],"cell":[59,70,116],"is":[60],"designed":[61],"enhance":[63],"such":[64,104],"relationship.":[65],"We":[66],"employ":[67],"this":[68],"novel":[69],"our":[72],"hybrid":[73],"attention":[74],"prediction":[75,130],"network.":[76],"new":[78],"structure":[79],"enriches":[80],"communication":[82],"message":[86],"embedding":[87],"current":[90],"signal,":[91],"hence":[92],"a":[93],"better":[94],"process":[96],"representation":[97],"compared":[98],"with":[99],"neural":[101],"network":[102],"without":[103],"mechanism.":[105],"Experiment":[106],"on":[107],"real-world":[108],"stock":[109],"data":[111],"shows":[112],"based":[115],"can":[117],"outperform":[118],"venerable":[120],"ones":[121],"across":[122],"different":[123],"sectors":[125],"while":[126],"still":[127],"achieves":[128],"lower":[129],"volatility.":[131]},"counts_by_year":[{"year":2024,"cited_by_count":1},{"year":2023,"cited_by_count":1}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}