{"id":"https://openalex.org/W2791788833","doi":"https://doi.org/10.1109/ialp.2017.8300622","title":"A hierarchical lstm model with multiple features for sentiment analysis of sina weibo texts","display_name":"A hierarchical lstm model with multiple features for sentiment analysis of sina weibo texts","publication_year":2017,"publication_date":"2017-12-01","ids":{"openalex":"https://openalex.org/W2791788833","doi":"https://doi.org/10.1109/ialp.2017.8300622","mag":"2791788833"},"language":"en","primary_location":{"id":"doi:10.1109/ialp.2017.8300622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ialp.2017.8300622","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Asian Language Processing (IALP)","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/A5037738790","display_name":"Shumin Shi","orcid":"https://orcid.org/0000-0003-3436-7575"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I4210139765","display_name":"Beijing Computing Center","ror":"https://ror.org/047r47y76","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210139765"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shumin Shi","raw_affiliation_strings":["Beijing Engineering Research Center of High Volume Language, Information Processing and Cloud Computing Applications, Beijing, China","School of Computer Science and Technology, Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center of High Volume Language, Information Processing and Cloud Computing Applications, Beijing, China","institution_ids":["https://openalex.org/I4210139765"]},{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5070105853","display_name":"Meng Zhao","orcid":"https://orcid.org/0000-0002-5060-9223"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Meng Zhao","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5065078725","display_name":"Jun Guan","orcid":null},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jun Guan","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5034854007","display_name":"Yaxuan Li","orcid":"https://orcid.org/0009-0007-6041-428X"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Yaxuan Li","raw_affiliation_strings":["School of Computer Science and Technology, Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5087631670","display_name":"Heyan Huang","orcid":"https://orcid.org/0000-0002-0320-7520"},"institutions":[{"id":"https://openalex.org/I125839683","display_name":"Beijing Institute of Technology","ror":"https://ror.org/01skt4w74","country_code":"CN","type":"education","lineage":["https://openalex.org/I125839683","https://openalex.org/I890469752"]},{"id":"https://openalex.org/I4210139765","display_name":"Beijing Computing Center","ror":"https://ror.org/047r47y76","country_code":"CN","type":"other","lineage":["https://openalex.org/I4210139765"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Heyan Huang","raw_affiliation_strings":["Beijing Engineering Research Center of High Volume Language, Information Processing and Cloud Computing Applications, Beijing, China","School of Computer Science and Technology, Beijing Institute of Technology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Beijing Engineering Research Center of High Volume Language, Information Processing and Cloud Computing Applications, Beijing, China","institution_ids":["https://openalex.org/I4210139765"]},{"raw_affiliation_string":"School of Computer Science and Technology, Beijing Institute of Technology","institution_ids":["https://openalex.org/I125839683"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":26,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"379","last_page":"382"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9995999932289124,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9995999932289124,"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/T13083","display_name":"Advanced Text Analysis Techniques","score":0.9937999844551086,"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":0.8700035810470581},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.7750329971313477},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.7253984808921814},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5829402208328247},{"id":"https://openalex.org/keywords/sentence","display_name":"Sentence","score":0.5756150484085083},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5386009812355042},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.5277707576751709},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.5267079472541809},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.5217264890670776},{"id":"https://openalex.org/keywords/recurrent-neural-network","display_name":"Recurrent neural network","score":0.4642302393913269},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46332141757011414},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3632885813713074},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.30731338262557983},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.09576189517974854}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8700035810470581},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.7750329971313477},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.7253984808921814},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5829402208328247},{"id":"https://openalex.org/C2777530160","wikidata":"https://www.wikidata.org/wiki/Q41796","display_name":"Sentence","level":2,"score":0.5756150484085083},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5386009812355042},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5277707576751709},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.5267079472541809},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.5217264890670776},{"id":"https://openalex.org/C147168706","wikidata":"https://www.wikidata.org/wiki/Q1457734","display_name":"Recurrent neural network","level":3,"score":0.4642302393913269},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46332141757011414},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3632885813713074},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.30731338262557983},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.09576189517974854},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","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},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/ialp.2017.8300622","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ialp.2017.8300622","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 International Conference on Asian Language Processing (IALP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"score":0.8199999928474426,"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"},{"id":"https://openalex.org/F4320327582","display_name":"Basic Research Foundation of Beijing Institute of Technology","ror":null}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":25,"referenced_works":["https://openalex.org/W22861983","https://openalex.org/W71795751","https://openalex.org/W1832693441","https://openalex.org/W1889268436","https://openalex.org/W2082358445","https://openalex.org/W2154359981","https://openalex.org/W2217066517","https://openalex.org/W2250879510","https://openalex.org/W2250966211","https://openalex.org/W2251292973","https://openalex.org/W2252215182","https://openalex.org/W2284289336","https://openalex.org/W2294007042","https://openalex.org/W2490887697","https://openalex.org/W2563010554","https://openalex.org/W2607310459","https://openalex.org/W2963921497","https://openalex.org/W2964331270","https://openalex.org/W6600949241","https://openalex.org/W6602989467","https://openalex.org/W6639364127","https://openalex.org/W6682839988","https://openalex.org/W6688248365","https://openalex.org/W6695662000","https://openalex.org/W6723060366"],"related_works":["https://openalex.org/W4225394202","https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W4298287631","https://openalex.org/W2953061907","https://openalex.org/W1847088711","https://openalex.org/W2596247554","https://openalex.org/W3036642985","https://openalex.org/W3008584592"],"abstract_inverted_index":{"Sentiment":[0],"analysis":[1,19,104],"has":[2],"long":[3],"been":[4,40],"a":[5,30,121],"hot":[6],"topic":[7],"in":[8,33],"natural":[9],"language":[10],"processing.":[11],"With":[12],"the":[13,60,64,79,96,105,136,139],"development":[14],"of":[15,68,114],"social":[16,21],"network,":[17],"sentiment":[18,43],"on":[20,73],"media":[22],"such":[23],"as":[24],"Facebook,":[25],"Twitter":[26],"and":[27,49,51,56,77,82,99,116,134,144,156],"Weibo":[28],"becomes":[29],"new":[31],"trend":[32],"recent":[34],"years.":[35],"Many":[36],"different":[37],"methods":[38,47,54,70],"have":[39],"proposed":[41],"for":[42],"analysis,":[44],"including":[45],"traditional":[46],"(SVM":[48],"NB)":[50],"deep":[52],"learning":[53],"(RNN":[55],"CNN).":[57],"In":[58,85],"addition,":[59],"latter":[61],"always":[62],"outperform":[63],"former.":[65],"However,":[66],"most":[67],"existing":[69],"only":[71],"focus":[72],"local":[74],"text":[75],"information":[76],"ignore":[78],"user":[80],"personality":[81],"content":[83],"characteristics.":[84],"this":[86],"paper,":[87],"we":[88,119],"propose":[89],"an":[90],"improved":[91],"LSTM":[92,123,129],"model":[93,130,140,153],"with":[94,131],"considering":[95],"user-based":[97,115],"features":[98,111,137],"content-based":[100],"features.":[101],"We":[102],"first":[103],"training":[106],"dataset":[107],"to":[108,141,160],"extract":[109],"artificial":[110],"which":[112],"consists":[113],"content-based.":[117],"Then":[118],"construct":[120],"hierarchical":[122,128],"model,":[124],"named":[125],"LSTM-MF":[126],"(a":[127],"multiple":[132],"features),":[133],"introduce":[135],"into":[138],"generate":[142],"sentence":[143],"document":[145],"representations.":[146],"The":[147],"experimental":[148],"results":[149],"show":[150],"that":[151],"our":[152],"achieves":[154],"significant":[155],"consistent":[157],"improvements":[158],"compared":[159],"all":[161],"state-of-the-art":[162],"methods.":[163]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":7},{"year":2023,"cited_by_count":6},{"year":2022,"cited_by_count":3},{"year":2021,"cited_by_count":4},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":1},{"year":2018,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}
