{"id":"https://openalex.org/W4406458826","doi":"https://doi.org/10.1109/bigdata62323.2024.10825174","title":"A Domain-Agnostic Neurosymbolic Approach for Big Social Data Analysis: Evaluating Mental Health Sentiment on Social Media during COVID-19","display_name":"A Domain-Agnostic Neurosymbolic Approach for Big Social Data Analysis: Evaluating Mental Health Sentiment on Social Media during COVID-19","publication_year":2024,"publication_date":"2024-12-15","ids":{"openalex":"https://openalex.org/W4406458826","doi":"https://doi.org/10.1109/bigdata62323.2024.10825174"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata62323.2024.10825174","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref","datacite"],"open_access":{"is_oa":true,"oa_status":"green","oa_url":"https://mdsoar.org/bitstreams/43dd5447-eebf-43ed-8779-134684e66a9e/download","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5110741656","display_name":"Vedant Khandelwal","orcid":null},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Vedant Khandelwal","raw_affiliation_strings":["University of South Carolina,AI Institute,Columbia,South Carolina"],"affiliations":[{"raw_affiliation_string":"University of South Carolina,AI Institute,Columbia,South Carolina","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5023667301","display_name":"Manas Gaur","orcid":"https://orcid.org/0000-0002-5411-2230"},"institutions":[{"id":"https://openalex.org/I66946132","display_name":"University of Maryland, College Park","ror":"https://ror.org/047s2c258","country_code":"US","type":"education","lineage":["https://openalex.org/I66946132"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Manas Gaur","raw_affiliation_strings":["University of Maryland,Department of Computer Science and Engineering,Maryland"],"affiliations":[{"raw_affiliation_string":"University of Maryland,Department of Computer Science and Engineering,Maryland","institution_ids":["https://openalex.org/I66946132"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101594465","display_name":"Ugur Kursuncu","orcid":"https://orcid.org/0000-0002-8108-9590"},"institutions":[{"id":"https://openalex.org/I181565077","display_name":"Georgia State University","ror":"https://ror.org/03qt6ba18","country_code":"US","type":"education","lineage":["https://openalex.org/I181565077"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Ugur Kursuncu","raw_affiliation_strings":["Georgia State University,Institute for Insight,Atlanta,Georgia"],"affiliations":[{"raw_affiliation_string":"Georgia State University,Institute for Insight,Atlanta,Georgia","institution_ids":["https://openalex.org/I181565077"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5108053995","display_name":"Valerie L. Shalin","orcid":"https://orcid.org/0000-0001-8135-2793"},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Valerie L. Shalin","raw_affiliation_strings":["University of South Carolina,AI Institute,Columbia,South Carolina"],"affiliations":[{"raw_affiliation_string":"University of South Carolina,AI Institute,Columbia,South Carolina","institution_ids":["https://openalex.org/I155781252"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5028772801","display_name":"Amit Sheth","orcid":null},"institutions":[{"id":"https://openalex.org/I155781252","display_name":"University of South Carolina","ror":"https://ror.org/02b6qw903","country_code":"US","type":"education","lineage":["https://openalex.org/I155781252"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amit P. Sheth","raw_affiliation_strings":["University of South Carolina,AI Institute,Columbia,South Carolina"],"affiliations":[{"raw_affiliation_string":"University of South Carolina,AI Institute,Columbia,South Carolina","institution_ids":["https://openalex.org/I155781252"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5110741656"],"corresponding_institution_ids":["https://openalex.org/I155781252"],"apc_list":null,"apc_paid":null,"fwci":3.1508,"has_fulltext":true,"cited_by_count":5,"citation_normalized_percentile":{"value":0.92059012,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"959","last_page":"968"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T12488","display_name":"Mental Health via Writing","score":0.9994000196456909,"subfield":{"id":"https://openalex.org/subfields/3207","display_name":"Social Psychology"},"field":{"id":"https://openalex.org/fields/32","display_name":"Psychology"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9961000084877014,"subfield":{"id":"https://openalex.org/subfields/3312","display_name":"Sociology and Political Science"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9957000017166138,"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/social-media","display_name":"Social media","score":0.7750098705291748},{"id":"https://openalex.org/keywords/big-data","display_name":"Big data","score":0.6992762684822083},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.6915746331214905},{"id":"https://openalex.org/keywords/coronavirus-disease-2019","display_name":"Coronavirus disease 2019 (COVID-19)","score":0.6590062379837036},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6253364086151123},{"id":"https://openalex.org/keywords/mental-health","display_name":"Mental health","score":0.5898716449737549},{"id":"https://openalex.org/keywords/data-science","display_name":"Data science","score":0.5850691795349121},{"id":"https://openalex.org/keywords/domain","display_name":"Domain (mathematical analysis)","score":0.4767516553401947},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2647777199745178},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.2510325312614441},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.23713156580924988},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.20531347393989563},{"id":"https://openalex.org/keywords/medicine","display_name":"Medicine","score":0.13996651768684387},{"id":"https://openalex.org/keywords/psychiatry","display_name":"Psychiatry","score":0.11687123775482178},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.07398974895477295}],"concepts":[{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.7750098705291748},{"id":"https://openalex.org/C75684735","wikidata":"https://www.wikidata.org/wiki/Q858810","display_name":"Big data","level":2,"score":0.6992762684822083},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.6915746331214905},{"id":"https://openalex.org/C3008058167","wikidata":"https://www.wikidata.org/wiki/Q84263196","display_name":"Coronavirus disease 2019 (COVID-19)","level":4,"score":0.6590062379837036},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6253364086151123},{"id":"https://openalex.org/C134362201","wikidata":"https://www.wikidata.org/wiki/Q317309","display_name":"Mental health","level":2,"score":0.5898716449737549},{"id":"https://openalex.org/C2522767166","wikidata":"https://www.wikidata.org/wiki/Q2374463","display_name":"Data science","level":1,"score":0.5850691795349121},{"id":"https://openalex.org/C36503486","wikidata":"https://www.wikidata.org/wiki/Q11235244","display_name":"Domain (mathematical analysis)","level":2,"score":0.4767516553401947},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2647777199745178},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.2510325312614441},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.23713156580924988},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.20531347393989563},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.13996651768684387},{"id":"https://openalex.org/C118552586","wikidata":"https://www.wikidata.org/wiki/Q7867","display_name":"Psychiatry","level":1,"score":0.11687123775482178},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.07398974895477295},{"id":"https://openalex.org/C142724271","wikidata":"https://www.wikidata.org/wiki/Q7208","display_name":"Pathology","level":1,"score":0.0},{"id":"https://openalex.org/C2779134260","wikidata":"https://www.wikidata.org/wiki/Q12136","display_name":"Disease","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C524204448","wikidata":"https://www.wikidata.org/wiki/Q788926","display_name":"Infectious disease (medical specialty)","level":3,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.1109/bigdata62323.2024.10825174","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata62323.2024.10825174","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2024 IEEE International Conference on Big Data (BigData)","raw_type":"proceedings-article"},{"id":"pmh:oai:mdsoar.org:11603/37106","is_oa":true,"landing_page_url":"http://hdl.handle.net/11603/37106","pdf_url":"https://mdsoar.org/bitstreams/43dd5447-eebf-43ed-8779-134684e66a9e/download","source":{"id":"https://openalex.org/S4306402556","display_name":"Maryland Shared Open Access Repository (USMAI Consortium)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},{"id":"doi:10.13016/m2lgbd-hp2e","is_oa":true,"landing_page_url":"https://doi.org/10.13016/m2lgbd-hp2e","pdf_url":null,"source":{"id":"https://openalex.org/S4306402644","display_name":"Digital Repository at the University of Maryland (University of Maryland College Park)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I66946132","host_organization_name":"University of Maryland, College Park","host_organization_lineage":["https://openalex.org/I66946132"],"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":"article-journal"}],"best_oa_location":{"id":"pmh:oai:mdsoar.org:11603/37106","is_oa":true,"landing_page_url":"http://hdl.handle.net/11603/37106","pdf_url":"https://mdsoar.org/bitstreams/43dd5447-eebf-43ed-8779-134684e66a9e/download","source":{"id":"https://openalex.org/S4306402556","display_name":"Maryland Shared Open Access Repository (USMAI Consortium)","issn_l":null,"issn":null,"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":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":null,"raw_type":"Text"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.550000011920929,"id":"https://metadata.un.org/sdg/10"}],"awards":[{"id":"https://openalex.org/G4049666403","display_name":null,"funder_award_id":"EAGER","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G6290369538","display_name":null,"funder_award_id":"2133842","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7114220319","display_name":"Spokes: MEDIUM: MIDWEST: Collaborative: Community-Driven Data Engineering for Substance Abuse Prevention in the Rural Midwest","funder_award_id":"1956009","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":true,"grobid_xml":false},"content_urls":{"pdf":"https://content.openalex.org/works/W4406458826.pdf"},"referenced_works_count":63,"referenced_works":["https://openalex.org/W68293321","https://openalex.org/W102264027","https://openalex.org/W600250629","https://openalex.org/W1499713768","https://openalex.org/W1552847225","https://openalex.org/W1614298861","https://openalex.org/W2015692847","https://openalex.org/W2080133951","https://openalex.org/W2132322340","https://openalex.org/W2250539671","https://openalex.org/W2404369708","https://openalex.org/W2460515658","https://openalex.org/W2520730796","https://openalex.org/W2561529111","https://openalex.org/W2611632661","https://openalex.org/W2896457183","https://openalex.org/W2897232984","https://openalex.org/W2963626623","https://openalex.org/W2998385486","https://openalex.org/W3003973800","https://openalex.org/W3087923126","https://openalex.org/W3094293990","https://openalex.org/W3095511143","https://openalex.org/W3105649132","https://openalex.org/W3110075606","https://openalex.org/W3113280695","https://openalex.org/W3126516789","https://openalex.org/W3175604467","https://openalex.org/W3206995115","https://openalex.org/W3216132400","https://openalex.org/W4206229917","https://openalex.org/W4213284163","https://openalex.org/W4231510805","https://openalex.org/W4251179700","https://openalex.org/W4283790718","https://openalex.org/W4285620502","https://openalex.org/W4288421382","https://openalex.org/W4289985951","https://openalex.org/W4293191267","https://openalex.org/W4294170691","https://openalex.org/W4295832344","https://openalex.org/W4311665646","https://openalex.org/W4311796245","https://openalex.org/W4322718191","https://openalex.org/W4376872682","https://openalex.org/W4380534756","https://openalex.org/W4382198109","https://openalex.org/W4386305073","https://openalex.org/W4393152448","https://openalex.org/W4406458826","https://openalex.org/W4413552952","https://openalex.org/W6636510571","https://openalex.org/W6639619044","https://openalex.org/W6682691769","https://openalex.org/W6689811036","https://openalex.org/W6713634263","https://openalex.org/W6726540210","https://openalex.org/W6755207826","https://openalex.org/W6770922693","https://openalex.org/W6785696047","https://openalex.org/W6787445178","https://openalex.org/W6850625674","https://openalex.org/W6941232018"],"related_works":["https://openalex.org/W2748952813","https://openalex.org/W4390608645","https://openalex.org/W4405901645","https://openalex.org/W4394895745","https://openalex.org/W4247566972","https://openalex.org/W2960264696","https://openalex.org/W3090563135","https://openalex.org/W2497432351","https://openalex.org/W4206777497","https://openalex.org/W2548633793"],"abstract_inverted_index":{"Monitoring":[0],"public":[1],"sentiment":[2],"via":[3],"social":[4,57],"media":[5,58],"is":[6],"potentially":[7,55],"helpful":[8],"during":[9],"health":[10,169],"crises":[11],"such":[12,45,167],"as":[13,46,168],"the":[14,32,77,153],"COVID-19":[15],"pandemic.":[16],"However,":[17],"traditional":[18],"frequency-based":[19],"and":[20,51,79,105,109,139],"data-driven":[21,122],"neural":[22,70],"network-based":[23],"approaches":[24],"can":[25,54],"miss":[26],"newly":[27],"relevant":[28,85],"content":[29],"due":[30],"to":[31,86,117,136],"evolving":[33,61,118],"nature":[34],"of":[35,81,95,155],"language":[36,50,147],"in":[37,60,158,161],"a":[38,65,93,162],"dynamic":[39,163],"environment.":[40],"Human-curated":[41],"symbolic":[42,73],"knowledge":[43,74,111],"sources,":[44,75],"lexicons":[47],"for":[48,165],"standard":[49],"slang":[52],"terms,":[53],"elevate":[56],"signals":[59],"language.":[62],"We":[63],"introduce":[64],"neurosymbolic":[66,156],"method":[67,89,114],"that":[68],"integrates":[69],"networks":[71],"with":[72,124],"improving":[76],"detection":[78],"interpretation":[80],"mental":[82],"health-related":[83],"tweets":[84],"COVID-19.":[87],"Our":[88],"was":[90],"evaluated":[91],"using":[92],"corpus":[94],"large":[96,146],"datasets":[97],"(~12":[98],"billion":[99],"tweets,":[100],"2.5":[101],"million":[102],"subreddit":[103],"data,":[104],"700k":[106],"news":[107],"articles)":[108],"multiple":[110],"graphs.":[112],"This":[113,130,150],"dynamically":[115],"adapts":[116],"language,":[119],"outperforming":[120],"purely":[121],"models":[123,148],"an":[125],"F1":[126],"score":[127],"exceeding":[128],"92%.":[129],"approach":[131],"also":[132],"showed":[133],"faster":[134],"adaptation":[135],"new":[137],"data":[138],"lower":[140],"computational":[141],"demands":[142],"than":[143],"fine-tuning":[144],"pre-trained":[145],"(LLMs).":[149],"study":[151],"demonstrates":[152],"benefit":[154],"methods":[157],"interpreting":[159],"text":[160],"environment":[164],"tasks":[166],"surveillance.":[170]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":1}],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}