{"id":"https://openalex.org/W6888580838","doi":"https://doi.org/10.21227/mfz7-4d65","title":"Multimodal Sentiment Analysis for Urdu Language","display_name":"Multimodal Sentiment Analysis for Urdu Language","publication_year":2023,"publication_date":"2023-10-18","ids":{"openalex":"https://openalex.org/W6888580838","doi":"https://doi.org/10.21227/mfz7-4d65"},"language":"en","primary_location":{"id":"doi:10.21227/mfz7-4d65","is_oa":true,"landing_page_url":"https://doi.org/10.21227/mfz7-4d65","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"type":"dataset","indexed_in":["datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://doi.org/10.21227/mfz7-4d65","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":null,"display_name":"Butt, Ghulam-Rabbani","orcid":null},"institutions":[],"countries":[],"is_corresponding":true,"raw_author_name":"Butt, Ghulam-Rabbani","raw_affiliation_strings":[],"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":true,"primary_topic":null,"topics":[],"keywords":[{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.8755000233650208},{"id":"https://openalex.org/keywords/urdu","display_name":"Urdu","score":0.6173999905586243},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.6044999957084656},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.46070000529289246},{"id":"https://openalex.org/keywords/natural-language","display_name":"Natural language","score":0.3831999897956848},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.3409000039100647}],"concepts":[{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.8755000233650208},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7587000131607056},{"id":"https://openalex.org/C2777350258","wikidata":"https://www.wikidata.org/wiki/Q1617","display_name":"Urdu","level":2,"score":0.6173999905586243},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.6044999957084656},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.5547999739646912},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.46070000529289246},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4099999964237213},{"id":"https://openalex.org/C195324797","wikidata":"https://www.wikidata.org/wiki/Q33742","display_name":"Natural language","level":2,"score":0.3831999897956848},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.3409000039100647},{"id":"https://openalex.org/C206345919","wikidata":"https://www.wikidata.org/wiki/Q20380951","display_name":"Resource (disambiguation)","level":2,"score":0.3197999894618988},{"id":"https://openalex.org/C2780583480","wikidata":"https://www.wikidata.org/wiki/Q1366327","display_name":"Tone (literature)","level":2,"score":0.3068999946117401},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.29899999499320984},{"id":"https://openalex.org/C2779308522","wikidata":"https://www.wikidata.org/wiki/Q843958","display_name":"Digitization","level":2,"score":0.2815999984741211},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.2784999907016754},{"id":"https://openalex.org/C155092808","wikidata":"https://www.wikidata.org/wiki/Q182557","display_name":"Computational linguistics","level":2,"score":0.2766000032424927},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.2734000086784363},{"id":"https://openalex.org/C162446236","wikidata":"https://www.wikidata.org/wiki/Q653137","display_name":"Content analysis","level":2,"score":0.2624000012874603}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.21227/mfz7-4d65","is_oa":true,"landing_page_url":"https://doi.org/10.21227/mfz7-4d65","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":null,"raw_source_name":null,"raw_type":"dataset"}],"best_oa_location":{"id":"doi:10.21227/mfz7-4d65","is_oa":true,"landing_page_url":"https://doi.org/10.21227/mfz7-4d65","pdf_url":null,"source":{"id":"https://openalex.org/S7407051695","display_name":"IEEE DataPort","issn_l":null,"issn":[],"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":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":null,"is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"dataset"},"sustainable_development_goals":[{"display_name":"Quality Education","id":"https://metadata.un.org/sdg/4","score":0.7686700224876404}],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":[],"abstract_inverted_index":{"The":[0,101,119,176,256,294,410],"\"Multi-modal":[1,332],"Sentiment":[2,333],"Analysis":[3,334],"Dataset":[4,335],"for":[5,206,285,313,336,348,376,396],"Urdu":[6,40,64,96,337,362],"Language":[7,338],"Opinion":[8,339],"Videos\"":[9,340],"is":[10,30,103,147,283,309,412],"a":[11,44,69,79,89,128,260,327,342,373],"valuable":[12],"resource":[13,312,347],"aimed":[14],"at":[15],"advancing":[16,377],"research":[17,209,378,421],"in":[18,50,116,135,263,280,326,351,379,404,429],"sentiment":[19,107,120,133,168,226,238,243,279,357,405],"analysis,":[20],"natural":[21],"language":[22,41,65,97],"processing,":[23],"and":[24,46,55,74,91,125,155,192,200,211,246,289,303,324,345,368,382,392,399,407,422],"multimedia":[25,137,251,306,328,385,408],"content":[26,48,98,182,252,267,287],"understanding.":[27,409],"This":[28,57],"dataset":[29,58,102,146,202,219,257,295,370,395,411],"specifically":[31],"curated":[32],"to":[33,35,158,161,220,272,316,390,418,423,425],"cater":[34,271],"the":[36,51,95,112,132,164,171,180,186,190,193,197,208,222,229,240,247,264,273,318,331,353,359,426,430],"unique":[37,142],"context":[38,172,230,360],"of":[39,63,72,78,81,85,94,131,144,167,173,183,189,225,231,242,249,266,276,356,361],"opinion":[42,66,138,174,232,281,363],"videos,":[43,67,83,191],"dynamic":[45,354],"influential":[47],"category":[49],"digital":[52],"landscape.Dataset":[53],"Description:Size":[54],"Diversity:":[56],"comprises":[59],"an":[60,310],"extensive":[61],"collection":[62],"encompassing":[68],"wide":[70],"spectrum":[71],"topics":[73],"sentiments.":[75],"It":[76,151,234,308],"consists":[77],"total":[80],"214":[82],"each":[84,117],"varying":[86],"lengths,":[87],"offering":[88,127],"diverse":[90,346],"comprehensive":[92],"representation":[93],"landscape.Sentiment":[99],"Annotations:":[100],"meticulously":[104],"annotated":[105],"with":[106,305,415],"labels,":[108],"providing":[109],"information":[110],"on":[111,300],"emotional":[113,274],"tone":[114],"expressed":[115],"video.":[118],"labels":[121],"include":[122],"\"positive,\"":[123],"\"negative,\"":[124],"\"neutral,\"":[126],"nuanced":[129],"understanding":[130],"conveyed":[134],"these":[136],"pieces.Multi-modal":[139],"Approach:":[140],"A":[141],"feature":[143],"this":[145,218,380,394],"its":[148],"multi-modal":[149,177,366],"approach.":[150],"combines":[152],"text,":[153],"audio,":[154],"visual":[156,194],"data":[157],"enable":[159],"researchers":[160,314,349],"delve":[162],"into":[163,237],"various":[165,397],"dimensions":[166],"analysis":[169,227,244,253,386,406],"within":[170,228,358],"videos.":[175,233,364],"annotations":[178,367],"encompass":[179],"textual":[181],"spoken":[184],"words,":[185],"auditory":[187],"characteristics":[188],"cues":[195],"from":[196],"video":[198],"frames.Significance":[199],"Applications:This":[201],"holds":[203],"significant":[204],"value":[205],"both":[207],"community":[210],"practical":[212],"applications:Research":[213],"Advancement:":[214],"Researchers":[215],"can":[216,258,296],"employ":[217],"investigate":[221],"complex":[223],"landscape":[224],"facilitates":[235],"inquiries":[236],"trends,":[239],"development":[241,265],"models,":[245],"creation":[248],"sentiment-aware":[250],"tools.Content":[254],"Recommendation:":[255],"play":[259],"pivotal":[261],"role":[262],"recommendation":[268],"systems":[269],"that":[270,320],"preferences":[275],"viewers.":[277],"Understanding":[278],"videos":[282],"crucial":[284],"improving":[286],"engagement":[288,302,325],"user":[290,301],"experience.User":[291],"Engagement":[292],"Analysis:":[293],"empower":[297],"studies":[298],"focused":[299],"interaction":[304],"content.":[307],"essential":[311],"aiming":[315],"decode":[317],"factors":[319],"influence":[321],"viewer":[322],"reactions":[323],"context.In":[329],"summary,":[330],"offers":[341],"unique,":[343],"comprehensive,":[344],"interested":[350],"exploring":[352],"world":[355],"Its":[365],"large":[369],"size":[371],"provide":[372],"robust":[374],"foundation":[375],"domain":[381],"developing":[383],"innovative":[384],"solutions.Researchers":[387],"are":[388],"encouraged":[389],"explore":[391],"utilize":[393],"academic":[398],"commercial":[400],"purposes,":[401],"fostering":[402],"innovation":[403],"made":[413],"available":[414],"open":[416],"access":[417],"facilitate":[419],"collaborative":[420],"contribute":[424],"broader":[427],"knowledge":[428],"field.  ":[431]},"counts_by_year":[{"year":2025,"cited_by_count":1}],"updated_date":"2025-11-06T06:51:31.235846","created_date":"2025-10-10T00:00:00"}