{"id":"https://openalex.org/W4389314685","doi":"https://doi.org/10.1145/3627377.3627388","title":"Graph Attention Network for Short Text Type News","display_name":"Graph Attention Network for Short Text Type News","publication_year":2023,"publication_date":"2023-09-22","ids":{"openalex":"https://openalex.org/W4389314685","doi":"https://doi.org/10.1145/3627377.3627388"},"language":"en","primary_location":{"id":"doi:10.1145/3627377.3627388","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627377.3627388","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3627377.3627388","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 6th International Conference on Big Data Technologies","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://dl.acm.org/doi/pdf/10.1145/3627377.3627388","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5025417954","display_name":"Zhijie Sun","orcid":"https://orcid.org/0000-0002-4864-5057"},"institutions":[{"id":"https://openalex.org/I34949971","display_name":"University of Jinan","ror":"https://ror.org/02mjz6f26","country_code":"CN","type":"education","lineage":["https://openalex.org/I34949971"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Zhijie Sun","raw_affiliation_strings":["School of Information Science and Engineering, University of Jinan, China and \rShandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, China"],"raw_orcid":"https://orcid.org/0000-0002-4864-5057","affiliations":[{"raw_affiliation_string":"School of Information Science and Engineering, University of Jinan, China and \rShandong Provincial Key Laboratory of Network Based Intelligent Computing, University of Jinan, China","institution_ids":["https://openalex.org/I34949971"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":["https://openalex.org/A5025417954"],"corresponding_institution_ids":["https://openalex.org/I34949971"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.18398178,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"66","last_page":"72"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10028","display_name":"Topic Modeling","score":0.9991000294685364,"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":0.9991000294685364,"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/T11273","display_name":"Advanced Graph Neural Networks","score":0.9979000091552734,"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":0.9972000122070312,"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":0.8113143444061279},{"id":"https://openalex.org/keywords/graph","display_name":"Graph","score":0.5947427749633789},{"id":"https://openalex.org/keywords/attention-network","display_name":"Attention network","score":0.5303319692611694},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.4663988947868347},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.41878002882003784},{"id":"https://openalex.org/keywords/theoretical-computer-science","display_name":"Theoretical computer science","score":0.37351155281066895},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3304939866065979},{"id":"https://openalex.org/keywords/computer-network","display_name":"Computer network","score":0.09834802150726318}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8113143444061279},{"id":"https://openalex.org/C132525143","wikidata":"https://www.wikidata.org/wiki/Q141488","display_name":"Graph","level":2,"score":0.5947427749633789},{"id":"https://openalex.org/C2993807640","wikidata":"https://www.wikidata.org/wiki/Q103709453","display_name":"Attention network","level":2,"score":0.5303319692611694},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.4663988947868347},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.41878002882003784},{"id":"https://openalex.org/C80444323","wikidata":"https://www.wikidata.org/wiki/Q2878974","display_name":"Theoretical computer science","level":1,"score":0.37351155281066895},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3304939866065979},{"id":"https://openalex.org/C31258907","wikidata":"https://www.wikidata.org/wiki/Q1301371","display_name":"Computer network","level":1,"score":0.09834802150726318}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3627377.3627388","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627377.3627388","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3627377.3627388","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 6th International Conference on Big Data Technologies","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.1145/3627377.3627388","is_oa":true,"landing_page_url":"https://doi.org/10.1145/3627377.3627388","pdf_url":"https://dl.acm.org/doi/pdf/10.1145/3627377.3627388","source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2023 6th International Conference on Big Data Technologies","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4389314685.pdf","grobid_xml":"https://content.openalex.org/works/W4389314685.grobid-xml"},"referenced_works_count":12,"referenced_works":["https://openalex.org/W1981276685","https://openalex.org/W2912642460","https://openalex.org/W2970398671","https://openalex.org/W2973114758","https://openalex.org/W3212763195","https://openalex.org/W4285249824","https://openalex.org/W6600005967","https://openalex.org/W6600195515","https://openalex.org/W6605614091","https://openalex.org/W6606298547","https://openalex.org/W6608040171","https://openalex.org/W6727875242"],"related_works":["https://openalex.org/W2366107444","https://openalex.org/W4388145910","https://openalex.org/W1976205134","https://openalex.org/W2381570729","https://openalex.org/W4248336175","https://openalex.org/W3009369890","https://openalex.org/W3200661810","https://openalex.org/W4389995241","https://openalex.org/W3213655484","https://openalex.org/W4320149722"],"abstract_inverted_index":{"In":[0],"the":[1,5,22,35,110,131,135,163,179,186,200],"era":[2],"of":[3,7,21,30,40,49,113,181,188,217],"self-media,":[4],"spread":[6],"fake":[8,50],"news":[9,32,41,51,68,132,158],"is":[10,80,154,166],"more":[11,75],"widespread":[12],"and":[13,38,73,86,126,138,175,191],"rapid":[14],"because":[15],"anyone":[16],"can":[17],"become":[18],"an":[19],"editor":[20],"news.":[23],"It":[24,53,79],"leads":[25],"to":[26,45,82,133,145],"a":[27,46,61,97,169],"large":[28],"number":[29],"short":[31,67],"texts.":[33],"However,":[34],"unchecked":[36],"dissemination":[37],"sharing":[39],"information":[42,129],"have":[43],"led":[44],"continuous":[47],"emergence":[48],"events.":[52],"not":[54],"only":[55,114],"misleads":[56],"readers":[57],"but":[58],"also":[59],"has":[60,95],"detrimental":[62],"impact":[63],"on":[64],"society.":[65],"Besides,":[66],"texts":[69],"are":[70],"semantically":[71],"sparse":[72],"need":[74],"contextual":[76],"solid":[77],"connections.":[78],"difficult":[81],"extract":[83],"text":[84,116,127,143],"features":[85,117,144],"achieve":[87],"high":[88],"error":[89],"detection":[90],"efficiency.":[91],"Therefore,":[92],"this":[93,204],"paper":[94,205],"proposed":[96,201],"heterogeneous":[98,164],"graph":[99,119,136,165],"attention":[100],"network":[101,108],"that":[102,199],"includes":[103],"multiple":[104],"text-related":[105],"features.":[106],"The":[107],"breaks":[109],"traditional":[111],"way":[112],"connecting":[115,150],"in":[118,156,203,215],"neural":[120],"networks,":[121],"extracts":[122],"various":[123],"external":[124,151],"knowledge":[125,152],"feature":[128],"from":[130],"construct":[134],"network,":[137],"establishes":[139],"connections":[140],"for":[141],"different":[142,182],"enhance":[146],"semantic":[147],"understanding.":[148],"Additionally,":[149],"bases":[153],"helpful":[155],"eliminating":[157],"entity":[159],"word":[160],"ambiguities.":[161],"Then,":[162],"embedded":[167],"into":[168],"dual-attention":[170],"mechanism":[171],"at":[172],"both":[173],"node":[174],"pattern":[176],"levels,":[177],"capturing":[178],"importance":[180],"adjacent":[183],"nodes,":[184,190],"reducing":[185],"weight":[187],"noisy":[189],"accurately":[192],"identifying":[193],"valid":[194],"information.":[195],"Experimental":[196],"results":[197],"demonstrate":[198],"method":[202],"outperforms":[206],"better":[207],"than":[208],"several":[209],"baseline":[210],"models,":[211],"such":[212],"as":[213],"TextGCN":[214],"terms":[216],"accuracy.":[218]},"counts_by_year":[],"updated_date":"2026-07-31T08:31:51.225901","created_date":"2025-10-10T00:00:00"}