{"id":"https://openalex.org/W2554987092","doi":"https://doi.org/10.1109/ijcnn.2016.7727784","title":"Sentic LDA: Improving on LDA with semantic similarity for aspect-based sentiment analysis","display_name":"Sentic LDA: Improving on LDA with semantic similarity for aspect-based sentiment analysis","publication_year":2016,"publication_date":"2016-07-01","ids":{"openalex":"https://openalex.org/W2554987092","doi":"https://doi.org/10.1109/ijcnn.2016.7727784","mag":"2554987092"},"language":"en","primary_location":{"id":"doi:10.1109/ijcnn.2016.7727784","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727784","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","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/A5033376109","display_name":"Soujanya Poria","orcid":"https://orcid.org/0000-0001-6924-7931"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":true,"raw_author_name":"Soujanya Poria","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5010637098","display_name":"Iti Chaturvedi","orcid":"https://orcid.org/0000-0003-4602-2080"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Iti Chaturvedi","raw_affiliation_strings":["Nanyang Technological University, Singapore, Singapore, SG"],"affiliations":[{"raw_affiliation_string":"Nanyang Technological University, Singapore, Singapore, SG","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100752356","display_name":"Erik Cambria","orcid":"https://orcid.org/0000-0002-3030-1280"},"institutions":[{"id":"https://openalex.org/I172675005","display_name":"Nanyang Technological University","ror":"https://ror.org/02e7b5302","country_code":"SG","type":"education","lineage":["https://openalex.org/I172675005"]}],"countries":["SG"],"is_corresponding":false,"raw_author_name":"Erik Cambria","raw_affiliation_strings":["School of Computer Science and Engineering, Nanyang Technological University, Singapore"],"affiliations":[{"raw_affiliation_string":"School of Computer Science and Engineering, Nanyang Technological University, Singapore","institution_ids":["https://openalex.org/I172675005"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5075110204","display_name":"Federica Bisio","orcid":null},"institutions":[{"id":"https://openalex.org/I83816512","display_name":"University of Genoa","ror":"https://ror.org/0107c5v14","country_code":"IT","type":"education","lineage":["https://openalex.org/I83816512"]}],"countries":["IT"],"is_corresponding":false,"raw_author_name":"Federica Bisio","raw_affiliation_strings":["DITEN University of Genoa, Italy"],"affiliations":[{"raw_affiliation_string":"DITEN University of Genoa, Italy","institution_ids":["https://openalex.org/I83816512"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5033376109"],"corresponding_institution_ids":["https://openalex.org/I172675005"],"apc_list":null,"apc_paid":null,"fwci":29.265,"has_fulltext":false,"cited_by_count":156,"citation_normalized_percentile":{"value":0.99597254,"is_in_top_1_percent":true,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":96,"max":100},"biblio":{"volume":null,"issue":null,"first_page":"4465","last_page":"4473"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9998999834060669,"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":0.9998999834060669,"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":0.9987000226974487,"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":0.9962999820709229,"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":0.8456047773361206},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.6458675861358643},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6437961459159851},{"id":"https://openalex.org/keywords/semantics","display_name":"Semantics (computer science)","score":0.5969745516777039},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5798584222793579},{"id":"https://openalex.org/keywords/cluster-analysis","display_name":"Cluster analysis","score":0.5673491358757019},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.4919709861278534},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.47816282510757446},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.47398748993873596},{"id":"https://openalex.org/keywords/word","display_name":"Word (group theory)","score":0.46950364112854004},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.468133807182312},{"id":"https://openalex.org/keywords/semantic-similarity","display_name":"Semantic similarity","score":0.44542351365089417},{"id":"https://openalex.org/keywords/information-extraction","display_name":"Information extraction","score":0.43539929389953613},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.4186166226863861},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.1318608522415161}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8456047773361206},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.6458675861358643},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6437961459159851},{"id":"https://openalex.org/C184337299","wikidata":"https://www.wikidata.org/wiki/Q1437428","display_name":"Semantics (computer science)","level":2,"score":0.5969745516777039},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5798584222793579},{"id":"https://openalex.org/C73555534","wikidata":"https://www.wikidata.org/wiki/Q622825","display_name":"Cluster analysis","level":2,"score":0.5673491358757019},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.4919709861278534},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.47816282510757446},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.47398748993873596},{"id":"https://openalex.org/C90805587","wikidata":"https://www.wikidata.org/wiki/Q10944557","display_name":"Word (group theory)","level":2,"score":0.46950364112854004},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.468133807182312},{"id":"https://openalex.org/C130318100","wikidata":"https://www.wikidata.org/wiki/Q2268914","display_name":"Semantic similarity","level":2,"score":0.44542351365089417},{"id":"https://openalex.org/C195807954","wikidata":"https://www.wikidata.org/wiki/Q1662562","display_name":"Information extraction","level":2,"score":0.43539929389953613},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.4186166226863861},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.1318608522415161},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"score":0.0},{"id":"https://openalex.org/C187736073","wikidata":"https://www.wikidata.org/wiki/Q2920921","display_name":"Management","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","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/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0}],"mesh":[],"locations_count":2,"locations":[{"id":"doi:10.1109/ijcnn.2016.7727784","is_oa":false,"landing_page_url":"https://doi.org/10.1109/ijcnn.2016.7727784","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2016 International Joint Conference on Neural Networks (IJCNN)","raw_type":"proceedings-article"},{"id":"pmh:oai:researchonline.jcu.edu.au:63353","is_oa":false,"landing_page_url":null,"pdf_url":null,"source":{"id":"https://openalex.org/S4306400519","display_name":"ResearchOnline at James Cook University (James Cook University)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I86467917","host_organization_name":"James Cook University","host_organization_lineage":["https://openalex.org/I86467917"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Conference Item"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","score":0.5099999904632568,"display_name":"Quality Education"}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":40,"referenced_works":["https://openalex.org/W1506246224","https://openalex.org/W1511480444","https://openalex.org/W1868188096","https://openalex.org/W1880262756","https://openalex.org/W1953362807","https://openalex.org/W1995207790","https://openalex.org/W1995866178","https://openalex.org/W2016196732","https://openalex.org/W2030439497","https://openalex.org/W2063698120","https://openalex.org/W2081375810","https://openalex.org/W2096110600","https://openalex.org/W2098062695","https://openalex.org/W2128507180","https://openalex.org/W2129604374","https://openalex.org/W2134297857","https://openalex.org/W2143027446","https://openalex.org/W2145071407","https://openalex.org/W2145768976","https://openalex.org/W2152571774","https://openalex.org/W2157589241","https://openalex.org/W2158085718","https://openalex.org/W2160409620","https://openalex.org/W2160660844","https://openalex.org/W2172083107","https://openalex.org/W2192604218","https://openalex.org/W2251777082","https://openalex.org/W2252057809","https://openalex.org/W2296734373","https://openalex.org/W2306941105","https://openalex.org/W2481359644","https://openalex.org/W3100922322","https://openalex.org/W4233135949","https://openalex.org/W4237730655","https://openalex.org/W6630417432","https://openalex.org/W6639619044","https://openalex.org/W6679076926","https://openalex.org/W6681597451","https://openalex.org/W6687074893","https://openalex.org/W6697591862"],"related_works":["https://openalex.org/W3089396779","https://openalex.org/W2548633793","https://openalex.org/W3013279174","https://openalex.org/W2941935829","https://openalex.org/W2596247554","https://openalex.org/W2754876402","https://openalex.org/W2531705611","https://openalex.org/W1837359179","https://openalex.org/W2165504147","https://openalex.org/W2986643010"],"abstract_inverted_index":{"The":[0],"advent":[1],"of":[2,31,42],"the":[3,29,35,79,89,155],"Social":[4],"Web":[5],"has":[6],"provided":[7],"netizens":[8],"with":[9,27,93,158],"new":[10],"tools":[11],"for":[12,51,171],"creating":[13],"and":[14,19,25,88,103,160],"sharing,":[15],"in":[16,85],"a":[17,65,86,138,141],"time-":[18],"cost-efficient":[20],"way,":[21],"their":[22,105],"contents,":[23],"ideas,":[24],"opinions":[26],"virtually":[28],"millions":[30],"people":[32],"connected":[33],"to":[34,63,72,116,133,140,163],"World":[36],"Wide":[37],"Web.":[38],"This":[39],"huge":[40],"amount":[41],"information,":[43],"however,":[44,100],"is":[45,57,108,114],"mainly":[46],"unstructured":[47,70],"as":[48],"specifically":[49],"produced":[50],"human":[52],"consumption":[53],"and,":[54,166],"hence,":[55,167],"it":[56],"not":[58],"directly":[59],"machine-processable.":[60],"In":[61],"order":[62],"enable":[64],"more":[66],"efficient":[67],"passage":[68],"from":[69,137],"information":[71],"structured":[73],"data,":[74],"aspect-based":[75],"opinion":[76,82],"mining":[77],"models":[78],"relations":[80],"between":[81],"targets":[83],"contained":[84],"document":[87],"polarity":[90,107],"values":[91],"associated":[92,157],"these.":[94],"Because":[95],"aspects":[96],"are":[97],"often":[98],"implicit,":[99],"spotting":[101],"them":[102],"calculating":[104],"respective":[106],"an":[109],"extremely":[110],"difficult":[111],"task,":[112],"which":[113],"closer":[115],"natural":[117,122],"language":[118,123],"understanding":[119],"rather":[120],"than":[121,145],"processing.":[124],"To":[125],"this":[126],"end,":[127],"Sentic":[128,151],"LDA":[129,135,152],"exploits":[130],"common-sense":[131],"reasoning":[132],"shift":[134],"clustering":[136,165],"syntactic":[139],"semantic":[142],"level.":[143],"Rather":[144],"looking":[146],"at":[147],"word":[148],"co-occurrence":[149],"frequencies,":[150],"leverages":[153],"on":[154],"semantics":[156],"words":[159],"multi-word":[161],"expressions":[162],"improve":[164],"outperform":[168],"state-of-the-art":[169],"techniques":[170],"aspect":[172],"extraction.":[173]},"counts_by_year":[{"year":2025,"cited_by_count":9},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":16},{"year":2022,"cited_by_count":15},{"year":2021,"cited_by_count":28},{"year":2020,"cited_by_count":18},{"year":2019,"cited_by_count":17},{"year":2018,"cited_by_count":21},{"year":2017,"cited_by_count":25},{"year":2016,"cited_by_count":3}],"updated_date":"2026-04-04T16:13:02.066488","created_date":"2025-10-10T00:00:00"}