{"id":"https://openalex.org/W2997221530","doi":"https://doi.org/10.1109/icis46139.2019.8940242","title":"Neural Network Analysis of Stock Price Based on News Corpus Impact","display_name":"Neural Network Analysis of Stock Price Based on News Corpus Impact","publication_year":2019,"publication_date":"2019-06-01","ids":{"openalex":"https://openalex.org/W2997221530","doi":"https://doi.org/10.1109/icis46139.2019.8940242","mag":"2997221530"},"language":"en","primary_location":{"id":"doi:10.1109/icis46139.2019.8940242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icis46139.2019.8940242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS)","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/A5102088010","display_name":"Weihua Xie","orcid":null},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Weihua Xie","raw_affiliation_strings":["Key Laboratory of Convergent Media and Intelligent Technology(Communication University of China),Ministry of Education School of Computer Science and Cybersecurity, Communication University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Convergent Media and Intelligent Technology(Communication University of China),Ministry of Education School of Computer Science and Cybersecurity, Communication University of China, Beijing, China","institution_ids":["https://openalex.org/I75689368"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5062793914","display_name":"Feng Shuang","orcid":"https://orcid.org/0000-0002-4733-4732"},"institutions":[{"id":"https://openalex.org/I75689368","display_name":"Communication University of China","ror":"https://ror.org/04facbs33","country_code":"CN","type":"education","lineage":["https://openalex.org/I75689368"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shuang Feng","raw_affiliation_strings":["Key Laboratory of Convergent Media and Intelligent Technology(Communication University of China),Ministry of Education School of Computer Science and Cybersecurity, Communication University of China, Beijing, China"],"affiliations":[{"raw_affiliation_string":"Key Laboratory of Convergent Media and Intelligent Technology(Communication University of China),Ministry of Education School of Computer Science and Cybersecurity, Communication University of China, Beijing, China","institution_ids":["https://openalex.org/I75689368"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5102088010"],"corresponding_institution_ids":["https://openalex.org/I75689368"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.20761435,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"329","last_page":"332"},"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/T11052","display_name":"Energy Load and Power Forecasting","score":0.9871000051498413,"subfield":{"id":"https://openalex.org/subfields/2208","display_name":"Electrical and Electronic Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11059","display_name":"Market Dynamics and Volatility","score":0.9772999882698059,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/grasp","display_name":"GRASP","score":0.7310242652893066},{"id":"https://openalex.org/keywords/stock","display_name":"Stock (firearms)","score":0.6106729507446289},{"id":"https://openalex.org/keywords/stock-exchange","display_name":"Stock exchange","score":0.5840839743614197},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.527376651763916},{"id":"https://openalex.org/keywords/stock-price","display_name":"Stock price","score":0.5105050802230835},{"id":"https://openalex.org/keywords/stock-market","display_name":"Stock market","score":0.49817442893981934},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4404948949813843},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4185539484024048},{"id":"https://openalex.org/keywords/business","display_name":"Business","score":0.3684875965118408},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2804206609725952},{"id":"https://openalex.org/keywords/economics","display_name":"Economics","score":0.26405003666877747},{"id":"https://openalex.org/keywords/finance","display_name":"Finance","score":0.2019086480140686}],"concepts":[{"id":"https://openalex.org/C171268870","wikidata":"https://www.wikidata.org/wiki/Q1486676","display_name":"GRASP","level":2,"score":0.7310242652893066},{"id":"https://openalex.org/C204036174","wikidata":"https://www.wikidata.org/wiki/Q909380","display_name":"Stock (firearms)","level":2,"score":0.6106729507446289},{"id":"https://openalex.org/C200870193","wikidata":"https://www.wikidata.org/wiki/Q11691","display_name":"Stock exchange","level":2,"score":0.5840839743614197},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.527376651763916},{"id":"https://openalex.org/C2988984586","wikidata":"https://www.wikidata.org/wiki/Q1020013","display_name":"Stock price","level":3,"score":0.5105050802230835},{"id":"https://openalex.org/C2780299701","wikidata":"https://www.wikidata.org/wiki/Q475000","display_name":"Stock market","level":3,"score":0.49817442893981934},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4404948949813843},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4185539484024048},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.3684875965118408},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2804206609725952},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.26405003666877747},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"score":0.2019086480140686},{"id":"https://openalex.org/C143724316","wikidata":"https://www.wikidata.org/wiki/Q312468","display_name":"Series (stratigraphy)","level":2,"score":0.0},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"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/C78519656","wikidata":"https://www.wikidata.org/wiki/Q101333","display_name":"Mechanical engineering","level":1,"score":0.0},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.0},{"id":"https://openalex.org/C2780762169","wikidata":"https://www.wikidata.org/wiki/Q5905368","display_name":"Horse","level":2,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icis46139.2019.8940242","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icis46139.2019.8940242","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE/ACIS 18th International Conference on Computer and Information Science (ICIS)","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":8,"referenced_works":["https://openalex.org/W1481342746","https://openalex.org/W2115839797","https://openalex.org/W2171556427","https://openalex.org/W2744043447","https://openalex.org/W2763060201","https://openalex.org/W2765762244","https://openalex.org/W2770436830","https://openalex.org/W2786274274"],"related_works":["https://openalex.org/W2370669686","https://openalex.org/W247222457","https://openalex.org/W1488120909","https://openalex.org/W3124131549","https://openalex.org/W3008476150","https://openalex.org/W2152348935","https://openalex.org/W2887069341","https://openalex.org/W2554106722","https://openalex.org/W1797892342","https://openalex.org/W4240248738"],"abstract_inverted_index":{"Investors":[0],"are":[1],"more":[2],"concerned":[3],"about":[4],"the":[5,23,27,29,32,36,44,47,50,55,62,66,71,76,80,87,94,105,122,129,148,158,172,183,192],"stock":[6,14,82,106,154,164,178,195],"prices":[7],"they":[8],"care":[9],"about.":[10],"The":[11,99,167],"trend":[12,179],"of":[13,26,31,38,41,46,54,79,96,101,108,128,136,150,174,185,194],"price":[15,107,165,196],"is":[16,110,180],"related":[17],"to":[18,43,74,162],"many":[19],"factors,":[20],"such":[21],"as":[22],"operation":[24,45],"status":[25],"enterprise,":[28,48],"heat":[30],"exchange":[33],"market":[34],"and":[35,49,52,124,132,140,147,156,182],"reaction":[37],"all":[39],"aspects":[40],"society":[42],"analysis":[51],"grasp":[53],"enterprise":[56],"information":[57,78,142],"by":[58],"individual":[59],"investors.":[60],"For":[61],"latter":[63],"two":[64],"items,":[65],"main":[67],"impact":[68,100],"comes":[69],"from":[70],"individual's":[72],"initiative":[73],"explore":[75],"trading":[77],"company's":[81],"situation,":[83],"which":[84],"results":[85,169],"in":[86],"purchase":[88],"intention.":[89],"This":[90],"paper":[91],"mainly":[92],"considers":[93],"influence":[95,149,173,189],"news":[97,102,175,187],"corpus.":[98],"corpus":[103,141,176,188],"on":[104,144,153,177],"enterprises":[109],"a":[111],"method":[112,184],"that":[113,171],"needs":[114],"quantitative":[115],"analysis.":[116],"In":[117],"this":[118],"paper,":[119],"we":[120],"adopt":[121],"independent":[123],"identical":[125],"distribution":[126],"model":[127],"positive":[130],"(positive)":[131],"negative":[133],"(negative)":[134],"attributes":[135,152],"lexical":[137],"frequency":[138],"classification":[139],"based":[143],"word":[145],"bag":[146],"social":[151],"price,":[155],"use":[157],"artificial":[159],"neural":[160],"network":[161],"calculate":[163],"parameters.":[166],"experimental":[168],"show":[170],"affirmative,":[181],"adding":[186],"effectively":[190],"improves":[191],"accuracy":[193],"prediction.":[197]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
