{"id":"https://openalex.org/W2890985598","doi":"https://doi.org/10.1162/coli_a_00338","title":"Combining Deep Learning and Argumentative Reasoning for the Analysis of Social Media Textual Content Using Small Data Sets","display_name":"Combining Deep Learning and Argumentative Reasoning for the Analysis of Social Media Textual Content Using Small Data Sets","publication_year":2018,"publication_date":"2018-09-18","ids":{"openalex":"https://openalex.org/W2890985598","doi":"https://doi.org/10.1162/coli_a_00338","mag":"2890985598"},"language":"en","primary_location":{"id":"doi:10.1162/coli_a_00338","is_oa":true,"landing_page_url":"https://doi.org/10.1162/coli_a_00338","pdf_url":"https://www.mitpressjournals.org/doi/pdf/10.1162/coli_a_00338","source":{"id":"https://openalex.org/S155526855","display_name":"Computational Linguistics","issn_l":"0891-2017","issn":["0891-2017","1530-9312"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Linguistics","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"diamond","oa_url":"https://www.mitpressjournals.org/doi/pdf/10.1162/coli_a_00338","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5034045968","display_name":"Oana Cocarascu","orcid":"https://orcid.org/0000-0003-1552-8636"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Oana Cocarascu","raw_affiliation_strings":["Imperial College London, Department of Computing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College London, Department of Computing","institution_ids":["https://openalex.org/I47508984"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078354590","display_name":"Francesca Toni","orcid":"https://orcid.org/0000-0001-8194-1459"},"institutions":[{"id":"https://openalex.org/I47508984","display_name":"Imperial College London","ror":"https://ror.org/041kmwe10","country_code":"GB","type":"education","lineage":["https://openalex.org/I47508984"]}],"countries":["GB"],"is_corresponding":true,"raw_author_name":"Francesca Toni","raw_affiliation_strings":["Imperial College London, Department of Computing"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Imperial College London, Department of Computing","institution_ids":["https://openalex.org/I47508984"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5034045968","https://openalex.org/A5078354590"],"corresponding_institution_ids":["https://openalex.org/I47508984"],"apc_list":null,"apc_paid":null,"fwci":3.0487,"has_fulltext":true,"cited_by_count":25,"citation_normalized_percentile":{"value":0.9324691,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":"44","issue":"4","first_page":"833","last_page":"858"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9993000030517578,"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/T10028","display_name":"Topic Modeling","score":0.9993000030517578,"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/T10260","display_name":"Software Engineering Research","score":0.9973000288009644,"subfield":{"id":"https://openalex.org/subfields/1710","display_name":"Information Systems"},"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.996999979019165,"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/argumentative","display_name":"Argumentative","score":0.9272594451904297},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.776183009147644},{"id":"https://openalex.org/keywords/argumentation-theory","display_name":"Argumentation theory","score":0.7259289026260376},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.6233249306678772},{"id":"https://openalex.org/keywords/deception","display_name":"Deception","score":0.6032459139823914},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.5670599937438965},{"id":"https://openalex.org/keywords/feature","display_name":"Feature (linguistics)","score":0.5554465055465698},{"id":"https://openalex.org/keywords/argument","display_name":"Argument (complex analysis)","score":0.5368965268135071},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5259785056114197},{"id":"https://openalex.org/keywords/task","display_name":"Task (project management)","score":0.518819272518158},{"id":"https://openalex.org/keywords/relation","display_name":"Relation (database)","score":0.5081472396850586},{"id":"https://openalex.org/keywords/argumentation-framework","display_name":"Argumentation framework","score":0.49790096282958984},{"id":"https://openalex.org/keywords/statement","display_name":"Statement (logic)","score":0.4867739677429199},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.46834796667099},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.42159369587898254},{"id":"https://openalex.org/keywords/feature-engineering","display_name":"Feature engineering","score":0.4214988052845001},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.41798287630081177},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.1714993715286255},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.16175591945648193},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.15041133761405945},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.13650187849998474},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.11446988582611084}],"concepts":[{"id":"https://openalex.org/C2781306805","wikidata":"https://www.wikidata.org/wiki/Q4789761","display_name":"Argumentative","level":2,"score":0.9272594451904297},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.776183009147644},{"id":"https://openalex.org/C65059942","wikidata":"https://www.wikidata.org/wiki/Q270105","display_name":"Argumentation theory","level":2,"score":0.7259289026260376},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.6233249306678772},{"id":"https://openalex.org/C2779267917","wikidata":"https://www.wikidata.org/wiki/Q170028","display_name":"Deception","level":2,"score":0.6032459139823914},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.5670599937438965},{"id":"https://openalex.org/C2776401178","wikidata":"https://www.wikidata.org/wiki/Q12050496","display_name":"Feature (linguistics)","level":2,"score":0.5554465055465698},{"id":"https://openalex.org/C98184364","wikidata":"https://www.wikidata.org/wiki/Q1780131","display_name":"Argument (complex analysis)","level":2,"score":0.5368965268135071},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5259785056114197},{"id":"https://openalex.org/C2780451532","wikidata":"https://www.wikidata.org/wiki/Q759676","display_name":"Task (project management)","level":2,"score":0.518819272518158},{"id":"https://openalex.org/C25343380","wikidata":"https://www.wikidata.org/wiki/Q277521","display_name":"Relation (database)","level":2,"score":0.5081472396850586},{"id":"https://openalex.org/C2779607372","wikidata":"https://www.wikidata.org/wiki/Q4789757","display_name":"Argumentation framework","level":3,"score":0.49790096282958984},{"id":"https://openalex.org/C2777026412","wikidata":"https://www.wikidata.org/wiki/Q2684591","display_name":"Statement (logic)","level":2,"score":0.4867739677429199},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.46834796667099},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.42159369587898254},{"id":"https://openalex.org/C2778827112","wikidata":"https://www.wikidata.org/wiki/Q22245680","display_name":"Feature engineering","level":3,"score":0.4214988052845001},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.41798287630081177},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.1714993715286255},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.16175591945648193},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.15041133761405945},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.13650187849998474},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.11446988582611084},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C162324750","wikidata":"https://www.wikidata.org/wiki/Q8134","display_name":"Economics","level":0,"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},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"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/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0}],"mesh":[],"locations_count":5,"locations":[{"id":"doi:10.1162/coli_a_00338","is_oa":true,"landing_page_url":"https://doi.org/10.1162/coli_a_00338","pdf_url":"https://www.mitpressjournals.org/doi/pdf/10.1162/coli_a_00338","source":{"id":"https://openalex.org/S155526855","display_name":"Computational Linguistics","issn_l":"0891-2017","issn":["0891-2017","1530-9312"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Linguistics","raw_type":"journal-article"},{"id":"pmh:oai:kclpure.kcl.ac.uk:openaire/75e27e4e-12ae-4a1c-82ae-9b0d96f46f0d","is_oa":false,"landing_page_url":"https://kclpure.kcl.ac.uk/portal/en/publications/75e27e4e-12ae-4a1c-82ae-9b0d96f46f0d","pdf_url":null,"source":{"id":"https://openalex.org/S4306400216","display_name":"Research Portal (King's College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I183935753","host_organization_name":"King's College London","host_organization_lineage":["https://openalex.org/I183935753"],"host_organization_lineage_names":[],"type":"repository"},"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Cocarascu, O & Toni, F 2018, 'Combining Deep Learning and Argumentative Reasoning for the Analysis of Social Media Textual Content Using Small Data Sets', COMPUTATIONAL LINGUISTICS, vol. 44, no. 4, pp. 833-858. https://doi.org/10.1162/coli_a_00338","raw_type":"info:eu-repo/semantics/publishedVersion"},{"id":"pmh:oai:kclpure.kcl.ac.uk:publications/75e27e4e-12ae-4a1c-82ae-9b0d96f46f0d","is_oa":true,"landing_page_url":"https://www.mitpressjournals.org/doi/abs/10.1162/coli_a_00338","pdf_url":"https://kclpure.kcl.ac.uk/ws/files/131683515/Combining_Deep_Learning_and_COCARASCU_Epub28Dec2018_GOLD_VoR_CC_BY_NC_ND_.pdf","source":null,"license":"other-oa","license_id":"https://openalex.org/licenses/other-oa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Cocarascu , O &amp; Toni , F 2018 , ' Combining Deep Learning and Argumentative Reasoning for the Analysis of Social Media Textual Content Using Small Data Sets ' , COMPUTATIONAL LINGUISTICS , vol. 44 , no. 4 , pp. 833-858 . https://doi.org/10.1162/coli_a_00338","raw_type":"article"},{"id":"pmh:oai:doaj.org/article:d3570cd0e54f4938b636ab4fe99cd9e8","is_oa":true,"landing_page_url":"https://doaj.org/article/d3570cd0e54f4938b636ab4fe99cd9e8","pdf_url":null,"source":{"id":"https://openalex.org/S4306401280","display_name":"DOAJ (DOAJ: Directory of Open Access Journals)","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-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Computational Linguistics, Vol 44, Iss 4, Pp 833-858 (2018)","raw_type":"article"},{"id":"pmh:oai:spiral.imperial.ac.uk:10044/1/63611","is_oa":true,"landing_page_url":"http://hdl.handle.net/10044/1/63611","pdf_url":null,"source":{"id":"https://openalex.org/S4306401396","display_name":"Spiral (Imperial College London)","issn_l":null,"issn":null,"is_oa":false,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I47508984","host_organization_name":"Imperial College London","host_organization_lineage":["https://openalex.org/I47508984"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"858","raw_type":"Journal Article"}],"best_oa_location":{"id":"doi:10.1162/coli_a_00338","is_oa":true,"landing_page_url":"https://doi.org/10.1162/coli_a_00338","pdf_url":"https://www.mitpressjournals.org/doi/pdf/10.1162/coli_a_00338","source":{"id":"https://openalex.org/S155526855","display_name":"Computational Linguistics","issn_l":"0891-2017","issn":["0891-2017","1530-9312"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310320244","host_organization_name":"Association for Computational Linguistics","host_organization_lineage":["https://openalex.org/P4310320244"],"host_organization_lineage_names":["Association for Computational Linguistics"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Computational Linguistics","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":true,"pdf":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2890985598.pdf","grobid_xml":"https://content.openalex.org/works/W2890985598.grobid-xml"},"referenced_works_count":78,"referenced_works":["https://openalex.org/W179875071","https://openalex.org/W1521626219","https://openalex.org/W1593138965","https://openalex.org/W1606218761","https://openalex.org/W1607035479","https://openalex.org/W1775665607","https://openalex.org/W1840435438","https://openalex.org/W1851422430","https://openalex.org/W1880262756","https://openalex.org/W1902027874","https://openalex.org/W1979504415","https://openalex.org/W1979822054","https://openalex.org/W2016266039","https://openalex.org/W2035896792","https://openalex.org/W2064675550","https://openalex.org/W2101234009","https://openalex.org/W2103063352","https://openalex.org/W2104126268","https://openalex.org/W2107878631","https://openalex.org/W2110453538","https://openalex.org/W2110485445","https://openalex.org/W2118463056","https://openalex.org/W2130324521","https://openalex.org/W2131555991","https://openalex.org/W2131774270","https://openalex.org/W2136710010","https://openalex.org/W2146007434","https://openalex.org/W2154058875","https://openalex.org/W2159359879","https://openalex.org/W2161283199","https://openalex.org/W2162317738","https://openalex.org/W2168231600","https://openalex.org/W2211192759","https://openalex.org/W2243249356","https://openalex.org/W2250299341","https://openalex.org/W2250539671","https://openalex.org/W2251030241","https://openalex.org/W2251048393","https://openalex.org/W2251645975","https://openalex.org/W2257979135","https://openalex.org/W2308720496","https://openalex.org/W2327805699","https://openalex.org/W2404406180","https://openalex.org/W2406121277","https://openalex.org/W2470673105","https://openalex.org/W2512040843","https://openalex.org/W2514892918","https://openalex.org/W2516171518","https://openalex.org/W2524556227","https://openalex.org/W2540268649","https://openalex.org/W2562273329","https://openalex.org/W2562522356","https://openalex.org/W2569238137","https://openalex.org/W2573400738","https://openalex.org/W2589020727","https://openalex.org/W2609722168","https://openalex.org/W2611470493","https://openalex.org/W2615337847","https://openalex.org/W2618530766","https://openalex.org/W2757512670","https://openalex.org/W2759690420","https://openalex.org/W2760347205","https://openalex.org/W2763486686","https://openalex.org/W2788370157","https://openalex.org/W2788538021","https://openalex.org/W2799915114","https://openalex.org/W2911964244","https://openalex.org/W2917458986","https://openalex.org/W2919115771","https://openalex.org/W2952980536","https://openalex.org/W2962878247","https://openalex.org/W2962958286","https://openalex.org/W2963403868","https://openalex.org/W2963591087","https://openalex.org/W2963731165","https://openalex.org/W2964121744","https://openalex.org/W4233384665","https://openalex.org/W4237791300"],"related_works":["https://openalex.org/W123909285","https://openalex.org/W4321448273","https://openalex.org/W1437497005","https://openalex.org/W4255580133","https://openalex.org/W2950795290","https://openalex.org/W2235416023","https://openalex.org/W3093095102","https://openalex.org/W1044030705","https://openalex.org/W1582835128","https://openalex.org/W2605884598"],"abstract_inverted_index":{"The":[0],"use":[1,78,110],"of":[2,72,143],"social":[3],"media":[4],"has":[5,13],"become":[6],"a":[7,60,88,98,101,149],"regular":[8],"habit":[9],"for":[10,64,81,113],"many":[11],"and":[12,34,74],"changed":[14],"the":[15,41,44,51,141,166],"way":[16],"people":[17],"interact":[18],"with":[19,158],"each":[20],"other.":[21],"In":[22,138],"this":[23,79],"article,":[24],"we":[25,58,109],"focus":[26],"on":[27,50,169],"analyzing":[28,40],"whether":[29,35,83,123],"news":[30,84],"headlines":[31],"support":[32,86],"tweets":[33],"reviews":[36,119],"are":[37,125],"deceptive":[38],"by":[39],"interaction":[42],"or":[43],"influence":[45],"that":[46,130],"these":[47],"texts":[48],"have":[49],"others,":[52],"thus":[53],"exploiting":[54],"contextual":[55],"information.":[56],"Concretely,":[57],"define":[59],"deep":[61],"learning":[62],"method":[63,80,112,132,147],"relation\u2013based":[65],"argument":[66],"mining":[67],"to":[68,120],"extract":[69],"argumentative":[70,151],"relations":[71],"attack":[73],"support.":[75],"We":[76,127],"then":[77],"determining":[82,95,105],"articles":[85],"tweets,":[87],"useful":[89,102],"task":[90],"in":[91,135,140,156,161],"fact-checking":[92],"settings,":[93],"where":[94],"agreement":[96],"toward":[97,104],"statement":[99],"is":[100],"step":[103],"its":[106],"truthfulness.":[107],"Furthermore,":[108],"our":[111,131,146],"extracting":[114],"bipolar":[115],"argumentation":[116],"frameworks":[117],"from":[118],"help":[121],"detect":[122],"they":[124],"deceptive.":[126],"show":[128],"experimentally":[129],"performs":[133],"well":[134],"both":[136],"settings.":[137],"particular,":[139],"case":[142],"deception":[144],"detection,":[145],"contributes":[148],"novel":[150],"feature":[152],"that,":[153],"when":[154],"used":[155],"combination":[157],"other":[159],"features":[160],"standard":[162],"supervised":[163],"classifiers,":[164],"outperforms":[165],"latter":[167],"even":[168],"small":[170],"data":[171],"sets.":[172]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2024,"cited_by_count":2},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":4},{"year":2021,"cited_by_count":7},{"year":2020,"cited_by_count":6},{"year":2019,"cited_by_count":4}],"updated_date":"2026-05-06T08:25:59.206177","created_date":"2025-10-10T00:00:00"}
