{"id":"https://openalex.org/W2961667864","doi":"https://doi.org/10.1109/cifer.2019.8759116","title":"Word-level Sentiment Visualizer for Financial Documents","display_name":"Word-level Sentiment Visualizer for Financial Documents","publication_year":2019,"publication_date":"2019-05-01","ids":{"openalex":"https://openalex.org/W2961667864","doi":"https://doi.org/10.1109/cifer.2019.8759116","mag":"2961667864"},"language":"en","primary_location":{"id":"doi:10.1109/cifer.2019.8759116","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cifer.2019.8759116","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr)","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/A5035683036","display_name":"Tomoki Ito","orcid":"https://orcid.org/0000-0003-4200-1311"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Tomoki Ito","raw_affiliation_strings":["Graduate School of Engineering, The University of Tokyo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5043621466","display_name":"Kota Tsubouchi","orcid":"https://orcid.org/0000-0002-7753-8939"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Kota Tsubouchi","raw_affiliation_strings":["Yahoo Japan Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yahoo Japan Corporation","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5028823648","display_name":"Hiroki Sakaji","orcid":"https://orcid.org/0000-0001-5030-625X"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Hiroki Sakaji","raw_affiliation_strings":["Graduate School of Engineering, The University of Tokyo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5030387579","display_name":"Tatsuo Yamashita","orcid":"https://orcid.org/0009-0007-2236-9633"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Tatsuo Yamashita","raw_affiliation_strings":["Yahoo Japan Corporation"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Yahoo Japan Corporation","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5044205949","display_name":"Kiyoshi Izumi","orcid":"https://orcid.org/0000-0003-0870-7310"},"institutions":[{"id":"https://openalex.org/I74801974","display_name":"The University of Tokyo","ror":"https://ror.org/057zh3y96","country_code":"JP","type":"education","lineage":["https://openalex.org/I74801974"]}],"countries":["JP"],"is_corresponding":false,"raw_author_name":"Kiyoshi Izumi","raw_affiliation_strings":["Graduate School of Engineering, The University of Tokyo"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Graduate School of Engineering, The University of Tokyo","institution_ids":["https://openalex.org/I74801974"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.07360925,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"15","issue":null,"first_page":"1","last_page":"7"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9955999851226807,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9955999851226807,"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":0.9952999949455261,"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/T11326","display_name":"Stock Market Forecasting Methods","score":0.9890000224113464,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.846740186214447},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6888648867607117},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.6567939519882202},{"id":"https://openalex.org/keywords/visualization","display_name":"Visualization","score":0.6143725514411926},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6072313189506531},{"id":"https://openalex.org/keywords/relevance","display_name":"Relevance (law)","score":0.49985456466674805},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4828129708766937},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.45962440967559814},{"id":"https://openalex.org/keywords/term","display_name":"Term (time)","score":0.4233197569847107},{"id":"https://openalex.org/keywords/tag-cloud","display_name":"Tag cloud","score":0.4159132242202759},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.15546661615371704}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.846740186214447},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6888648867607117},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.6567939519882202},{"id":"https://openalex.org/C36464697","wikidata":"https://www.wikidata.org/wiki/Q451553","display_name":"Visualization","level":2,"score":0.6143725514411926},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6072313189506531},{"id":"https://openalex.org/C158154518","wikidata":"https://www.wikidata.org/wiki/Q7310970","display_name":"Relevance (law)","level":2,"score":0.49985456466674805},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4828129708766937},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.45962440967559814},{"id":"https://openalex.org/C61797465","wikidata":"https://www.wikidata.org/wiki/Q1188986","display_name":"Term (time)","level":2,"score":0.4233197569847107},{"id":"https://openalex.org/C26983874","wikidata":"https://www.wikidata.org/wiki/Q263864","display_name":"Tag cloud","level":3,"score":0.4159132242202759},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.15546661615371704},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.0},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/cifer.2019.8759116","is_oa":false,"landing_page_url":"https://doi.org/10.1109/cifer.2019.8759116","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2019 IEEE Conference on Computational Intelligence for Financial Engineering & Economics (CIFEr)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[{"id":"https://openalex.org/F4320334764","display_name":"Japan Society for the Promotion of Science","ror":"https://ror.org/00hhkn466"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":49,"referenced_works":["https://openalex.org/W1494336933","https://openalex.org/W1522301498","https://openalex.org/W1570505288","https://openalex.org/W1589554437","https://openalex.org/W1787224781","https://openalex.org/W1976090620","https://openalex.org/W2016268421","https://openalex.org/W2022204871","https://openalex.org/W2064459199","https://openalex.org/W2064659890","https://openalex.org/W2075038621","https://openalex.org/W2095705004","https://openalex.org/W2112021086","https://openalex.org/W2113097878","https://openalex.org/W2115035636","https://openalex.org/W2122580360","https://openalex.org/W2123045220","https://openalex.org/W2131774270","https://openalex.org/W2134264955","https://openalex.org/W2150376021","https://openalex.org/W2152096672","https://openalex.org/W2153579005","https://openalex.org/W2167443668","https://openalex.org/W2282821441","https://openalex.org/W2513699236","https://openalex.org/W2514299353","https://openalex.org/W2539135795","https://openalex.org/W2552204443","https://openalex.org/W2552901897","https://openalex.org/W2562979205","https://openalex.org/W2594633041","https://openalex.org/W2605409611","https://openalex.org/W2741783618","https://openalex.org/W2773524130","https://openalex.org/W2951501516","https://openalex.org/W2962851944","https://openalex.org/W2963382180","https://openalex.org/W2964045325","https://openalex.org/W2964216356","https://openalex.org/W4294170691","https://openalex.org/W6635364467","https://openalex.org/W6641757719","https://openalex.org/W6674330103","https://openalex.org/W6677995690","https://openalex.org/W6679834832","https://openalex.org/W6682691769","https://openalex.org/W6684050557","https://openalex.org/W6734194636","https://openalex.org/W6736518430"],"related_works":["https://openalex.org/W2745862583","https://openalex.org/W2896245874","https://openalex.org/W2741843760","https://openalex.org/W3135449691","https://openalex.org/W2091262745","https://openalex.org/W2803988148","https://openalex.org/W2113459411","https://openalex.org/W2759864339","https://openalex.org/W2566238543","https://openalex.org/W2666029849","https://openalex.org/W2062913298","https://openalex.org/W2612939437","https://openalex.org/W2969519670","https://openalex.org/W2780842565","https://openalex.org/W1814871654","https://openalex.org/W2148171167","https://openalex.org/W2905230178","https://openalex.org/W2138260386","https://openalex.org/W2328290429","https://openalex.org/W2229404717"],"abstract_inverted_index":{"It":[0],"has":[1],"a":[2,31,48,63,69,77,169],"great":[3],"demand":[4],"for":[5,33,79,192],"automatically":[6,34],"visualizing":[7,35],"word-level":[8,38,41,53,56,85,146,152,163,178],"sentiment":[9,39,42,54,57,86,147,153,164],"scores":[10,87],"in":[11,14,47,62,68,106,114,168,182],"financial":[12,124,194],"documents":[13,181,195],"the":[15,36,45,51,60,91,103,117,129],"form":[16],"that":[17],"even":[18],"non-experts":[19],"can":[20,101],"briefly":[21],"understand":[22],"documents.":[23],"In":[24],"this":[25,73],"paper,":[26],"we":[27,75,127,137],"aim":[28],"to":[29,88,112,116],"develop":[30,76],"method":[32,78],"original":[37,82,108,160,175],"(i.e.,":[40,55],"before":[43],"considering":[44,59],"contexts":[46,61],"document)":[49,64],"and":[50,83,109,122,150,161,176],"contextual":[52,84,104,110,162,177],"after":[58],"of":[65,131,141,165,180,187],"each":[66,166],"term":[67,167],"document.":[70,170],"To":[71],"achieve":[72],"aim,":[74],"assigning":[80,107],"both":[81,159,174],"words":[89],"using":[90],"Layer-wise":[92],"Relevance":[93],"Propagation":[94],"(LRP)":[95],"method.":[96],"The":[97,156,171],"LRP":[98,133],"based":[99,134],"approach":[100],"consider":[102],"information":[105],"sentiments":[111,179],"words,":[113],"contrast":[115],"other":[118],"approaches.":[119],"Using":[120],"synthetic":[121],"real":[123],"textual":[125],"datasets,":[126],"demonstrated":[128],"validity":[130],"our":[132],"approach.":[135],"Moreover,":[136],"propose":[138],"two":[139],"types":[140,186],"novel":[142],"text-visualization":[143,188],"frameworks:":[144],"local":[145],"visualization":[148,154],"(LWSV)":[149],"global":[151],"(GWSV).":[155],"LWSV":[157],"visualizes":[158,173],"GWSV":[172],"concept":[183],"units.":[184],"These":[185],"should":[189],"be":[190],"helpful":[191],"understanding":[193],"quickly.":[196]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}