{"id":"https://openalex.org/W4382284402","doi":"https://doi.org/10.1145/3584871.3584873","title":"How to Find Social Robots exactly?","display_name":"How to Find Social Robots exactly?","publication_year":2023,"publication_date":"2023-01-31","ids":{"openalex":"https://openalex.org/W4382284402","doi":"https://doi.org/10.1145/3584871.3584873"},"language":"en","primary_location":{"id":"doi:10.1145/3584871.3584873","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3584871.3584873","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 The 6th International Conference on Software Engineering and Information Management","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/A5037774096","display_name":"Jianwei Ding","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Jianwei Ding","raw_affiliation_strings":["CETC 30, China"],"raw_orcid":"https://orcid.org/0000-0001-8441-4654","affiliations":[{"raw_affiliation_string":"CETC 30, China","institution_ids":[]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5003071181","display_name":"Zhouguo Chen","orcid":"https://orcid.org/0000-0002-4063-963X"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Zhouguo Chen","raw_affiliation_strings":["CETC 30, China"],"raw_orcid":"https://orcid.org/0000-0002-4063-963X","affiliations":[{"raw_affiliation_string":"CETC 30, China","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.11521653,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":null,"issue":null,"first_page":"12","last_page":"18"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9988999962806702,"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"}},"topics":[{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9988999962806702,"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/T10028","display_name":"Topic Modeling","score":0.9966999888420105,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9933000206947327,"subfield":{"id":"https://openalex.org/subfields/1705","display_name":"Computer Networks and Communications"},"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/metadata","display_name":"Metadata","score":0.8613001704216003},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8004149198532104},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.6309385299682617},{"id":"https://openalex.org/keywords/robot","display_name":"Robot","score":0.5839380025863647},{"id":"https://openalex.org/keywords/discriminative-model","display_name":"Discriminative model","score":0.5164194703102112},{"id":"https://openalex.org/keywords/crawling","display_name":"Crawling","score":0.5141713619232178},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4815519154071808},{"id":"https://openalex.org/keywords/social-network","display_name":"Social network (sociolinguistics)","score":0.4736327528953552},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.4618702232837677},{"id":"https://openalex.org/keywords/embedding","display_name":"Embedding","score":0.4614642262458801},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.45677298307418823},{"id":"https://openalex.org/keywords/exploit","display_name":"Exploit","score":0.4359026849269867},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.33642131090164185},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.32850295305252075},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.24257954955101013}],"concepts":[{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.8613001704216003},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8004149198532104},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.6309385299682617},{"id":"https://openalex.org/C90509273","wikidata":"https://www.wikidata.org/wiki/Q11012","display_name":"Robot","level":2,"score":0.5839380025863647},{"id":"https://openalex.org/C97931131","wikidata":"https://www.wikidata.org/wiki/Q5282087","display_name":"Discriminative model","level":2,"score":0.5164194703102112},{"id":"https://openalex.org/C100368936","wikidata":"https://www.wikidata.org/wiki/Q1411725","display_name":"Crawling","level":2,"score":0.5141713619232178},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4815519154071808},{"id":"https://openalex.org/C4727928","wikidata":"https://www.wikidata.org/wiki/Q17164759","display_name":"Social network (sociolinguistics)","level":3,"score":0.4736327528953552},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.4618702232837677},{"id":"https://openalex.org/C41608201","wikidata":"https://www.wikidata.org/wiki/Q980509","display_name":"Embedding","level":2,"score":0.4614642262458801},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.45677298307418823},{"id":"https://openalex.org/C165696696","wikidata":"https://www.wikidata.org/wiki/Q11287","display_name":"Exploit","level":2,"score":0.4359026849269867},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.33642131090164185},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.32850295305252075},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.24257954955101013},{"id":"https://openalex.org/C38652104","wikidata":"https://www.wikidata.org/wiki/Q3510521","display_name":"Computer security","level":1,"score":0.0},{"id":"https://openalex.org/C105702510","wikidata":"https://www.wikidata.org/wiki/Q514","display_name":"Anatomy","level":1,"score":0.0},{"id":"https://openalex.org/C71924100","wikidata":"https://www.wikidata.org/wiki/Q11190","display_name":"Medicine","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3584871.3584873","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3584871.3584873","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2023 The 6th International Conference on Software Engineering and Information Management","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/10","score":0.75,"display_name":"Reduced inequalities"}],"awards":[{"id":"https://openalex.org/G6000451536","display_name":null,"funder_award_id":"62172324","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":16,"referenced_works":["https://openalex.org/W1744901186","https://openalex.org/W2567791345","https://openalex.org/W2595521492","https://openalex.org/W2767370829","https://openalex.org/W2787296320","https://openalex.org/W2907352650","https://openalex.org/W2912554055","https://openalex.org/W2997788455","https://openalex.org/W3035082952","https://openalex.org/W3041367927","https://openalex.org/W3093798014","https://openalex.org/W3098680549","https://openalex.org/W3102083609","https://openalex.org/W3106311261","https://openalex.org/W3110578481","https://openalex.org/W3125928061"],"related_works":["https://openalex.org/W4321258516","https://openalex.org/W2051833850","https://openalex.org/W4287845917","https://openalex.org/W3156164993","https://openalex.org/W2385015894","https://openalex.org/W2171573941","https://openalex.org/W2144007828","https://openalex.org/W3040878054","https://openalex.org/W2766789703","https://openalex.org/W1588356406"],"abstract_inverted_index":{"With":[0,99],"the":[1,20,65,71,90,100,145,153,157,161,182,204,225,257],"rapid":[2],"development":[3],"of":[4,38,102,137,160,217,228,241,284],"artificial":[5,49],"intelligence":[6,50],"and":[7,14,131,164,177,186,212,223,232,243,281],"natural":[8],"language":[9,104],"processing,":[10],"there":[11],"are":[12,59,85],"more":[13,15,168],"social":[16,21,40,45,66,73,79,206,219,260],"robots":[17,67,207],"applied":[18,69,86],"in":[19,199,210],"networks":[22],"such":[23,106,148],"as":[24,107,149,249],"Twitter,":[25],"intended":[26],"to":[27,53,63,70,87,151,172,192,221,256],"lead":[28],"public":[29],"opinion":[30],"or":[31,93],"crawling":[32],"private":[33],"information":[34],"illegally.":[35],"The":[36,135,267],"problem":[37],"detection":[39],"robots,":[41],"which":[42,127],"is":[43],"automated":[44],"accounts":[46],"governed":[47],"by":[48,89],"software,":[51],"pretend":[52],"be":[54],"a":[55,112,174,194,214,279],"human":[56],"user.":[57],"There":[58],"some":[60],"technologies":[61,82],"proposed":[62,83,209,230],"detect":[64,88],"automatically":[68],"real":[72],"network":[74,115],"for":[75],"verification.":[76],"Hence,":[77],"conventional":[78,234],"robot":[80,261],"detecting":[81,195],"before":[84],"account's":[91,132],"metadata":[92,133,171,175,187],"account":[94,170],"posted":[95],"tweet":[96,129,158],"content":[97,130,159],"respectively.":[98],"help":[101],"pre-trained":[103],"model":[105,116,147],"BERT,":[108],"this":[109,200],"paper":[110],"propose":[111],"deep":[113],"neural":[114],"based":[117],"on":[118],"contextual":[119],"long":[120],"short-term":[121],"memory":[122],"(LSTM)":[123],"architecture":[124,136],"named":[125],"DeepBot,":[126],"exploits":[128],"features.":[134,285],"DeepBot":[138,231,242,272],"contains":[139],"three":[140],"phases:":[141],"(1)":[142],"it":[143,166,180,255],"uses":[144],"pretrained":[146],"BERT":[150],"extract":[152,173],"embedding":[154,184],"vector":[155,185,188],"from":[156],"specific":[162],"account,":[163],"(2)":[165],"choose":[167],"discriminative":[169],"vector,":[176],"then":[178],"(3)":[179],"combines":[181],"auxiliary":[183],"into":[189],"decoder":[190],"layer":[191],"train":[193],"model.":[196],"What's":[197],"more,":[198],"paper,":[201],"we":[202,250],"review":[203],"labelling":[205,218],"datasets":[208,216,220],"public,":[211],"get":[213],"mixture":[215,258],"verify":[222],"compare":[224],"experimental":[226,268],"results":[227,240,269],"our":[229,244],"other":[233],"methods.":[235],"We":[236],"also":[237],"present":[238],"empirical":[239],"ongoing":[245],"experimentation":[246],"with":[247,277],"it,":[248],"have":[251],"gained":[252],"experience":[253],"applying":[254],"labeling":[259],"dataset,":[262],"including":[263],"over":[264],"10000":[265],"accounts.":[266],"show":[270],"that":[271],"outperforms":[273],"previous":[274],"state-of-the-art":[275],"methods,":[276],"leveraging":[278],"small":[280],"interpretable":[282],"set":[283]},"counts_by_year":[],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}