{"id":"https://openalex.org/W2951128894","doi":"https://doi.org/10.18653/v1/p19-1270","title":"Joint Effects of Context and User History for Predicting Online Conversation Re-entries","display_name":"Joint Effects of Context and User History for Predicting Online Conversation Re-entries","publication_year":2019,"publication_date":"2019-01-01","ids":{"openalex":"https://openalex.org/W2951128894","doi":"https://doi.org/10.18653/v1/p19-1270","mag":"2951128894"},"language":"en","primary_location":{"id":"doi:10.18653/v1/p19-1270","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1270","pdf_url":"https://www.aclweb.org/anthology/P19-1270.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"type":"preprint","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/P19-1270.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5044933782","display_name":"Xingshan Zeng","orcid":"https://orcid.org/0000-0002-0455-5519"},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]},{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Xingshan Zeng","raw_affiliation_strings":["MoE Key Laboratory of High Confidence Software Technologies, China","The Chinese University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"MoE Key Laboratory of High Confidence Software Technologies, China","institution_ids":["https://openalex.org/I4210128818"]},{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100336998","display_name":"Jing Li","orcid":"https://orcid.org/0000-0002-8044-2284"},"institutions":[{"id":"https://openalex.org/I2250653659","display_name":"Tencent (China)","ror":"https://ror.org/00hhjss72","country_code":"CN","type":"company","lineage":["https://openalex.org/I2250653659"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Jing Li","raw_affiliation_strings":["Tencent AI Lab, Shenzhen, China"],"affiliations":[{"raw_affiliation_string":"Tencent AI Lab, Shenzhen, China","institution_ids":["https://openalex.org/I2250653659"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5100364523","display_name":"Lu Wang","orcid":"https://orcid.org/0000-0003-1688-5264"},"institutions":[{"id":"https://openalex.org/I12912129","display_name":"Northeastern University","ror":"https://ror.org/04t5xt781","country_code":"US","type":"education","lineage":["https://openalex.org/I12912129"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Lu Wang","raw_affiliation_strings":["Northeastern University, Boston, MA, United States"],"affiliations":[{"raw_affiliation_string":"Northeastern University, Boston, MA, United States","institution_ids":["https://openalex.org/I12912129"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5008208316","display_name":"Kam\u2010Fai Wong","orcid":"https://orcid.org/0000-0002-9427-5659"},"institutions":[{"id":"https://openalex.org/I4210128818","display_name":"Institute of Software","ror":"https://ror.org/033dfsn42","country_code":"CN","type":"facility","lineage":["https://openalex.org/I19820366","https://openalex.org/I4210128818"]},{"id":"https://openalex.org/I177725633","display_name":"Chinese University of Hong Kong","ror":"https://ror.org/00t33hh48","country_code":"CN","type":"education","lineage":["https://openalex.org/I177725633"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kam-Fai Wong","raw_affiliation_strings":["MoE Key Laboratory of High Confidence Software Technologies, China","The Chinese University of Hong Kong, Hong Kong"],"affiliations":[{"raw_affiliation_string":"MoE Key Laboratory of High Confidence Software Technologies, China","institution_ids":["https://openalex.org/I4210128818"]},{"raw_affiliation_string":"The Chinese University of Hong Kong, Hong Kong","institution_ids":["https://openalex.org/I177725633"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5044933782"],"corresponding_institution_ids":["https://openalex.org/I177725633","https://openalex.org/I4210128818"],"apc_list":null,"apc_paid":null,"fwci":1.4399,"has_fulltext":true,"cited_by_count":12,"citation_normalized_percentile":{"value":0.81872976,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":90,"max":98},"biblio":{"volume":null,"issue":null,"first_page":"2809","last_page":"2818"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11147","display_name":"Misinformation and Its Impacts","score":0.9988999962806702,"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9979000091552734,"subfield":{"id":"https://openalex.org/subfields/3109","display_name":"Statistical and Nonlinear Physics"},"field":{"id":"https://openalex.org/fields/31","display_name":"Physics and Astronomy"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/conversation","display_name":"Conversation","score":0.919194221496582},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.7366894483566284},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.7147283554077148},{"id":"https://openalex.org/keywords/interpersonal-communication","display_name":"Interpersonal communication","score":0.6969649791717529},{"id":"https://openalex.org/keywords/affect","display_name":"Affect (linguistics)","score":0.5757666826248169},{"id":"https://openalex.org/keywords/order","display_name":"Order (exchange)","score":0.4535830616950989},{"id":"https://openalex.org/keywords/human\u2013computer-interaction","display_name":"Human\u2013computer interaction","score":0.4301186203956604},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.39155954122543335},{"id":"https://openalex.org/keywords/psychology","display_name":"Psychology","score":0.23601430654525757},{"id":"https://openalex.org/keywords/social-psychology","display_name":"Social psychology","score":0.14737683534622192},{"id":"https://openalex.org/keywords/communication","display_name":"Communication","score":0.12552201747894287},{"id":"https://openalex.org/keywords/history","display_name":"History","score":0.07565170526504517}],"concepts":[{"id":"https://openalex.org/C2777200299","wikidata":"https://www.wikidata.org/wiki/Q52943","display_name":"Conversation","level":2,"score":0.919194221496582},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7366894483566284},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.7147283554077148},{"id":"https://openalex.org/C164850336","wikidata":"https://www.wikidata.org/wiki/Q3685487","display_name":"Interpersonal communication","level":2,"score":0.6969649791717529},{"id":"https://openalex.org/C2776035688","wikidata":"https://www.wikidata.org/wiki/Q1606558","display_name":"Affect (linguistics)","level":2,"score":0.5757666826248169},{"id":"https://openalex.org/C182306322","wikidata":"https://www.wikidata.org/wiki/Q1779371","display_name":"Order (exchange)","level":2,"score":0.4535830616950989},{"id":"https://openalex.org/C107457646","wikidata":"https://www.wikidata.org/wiki/Q207434","display_name":"Human\u2013computer interaction","level":1,"score":0.4301186203956604},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.39155954122543335},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.23601430654525757},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.14737683534622192},{"id":"https://openalex.org/C46312422","wikidata":"https://www.wikidata.org/wiki/Q11024","display_name":"Communication","level":1,"score":0.12552201747894287},{"id":"https://openalex.org/C95457728","wikidata":"https://www.wikidata.org/wiki/Q309","display_name":"History","level":0,"score":0.07565170526504517},{"id":"https://openalex.org/C10138342","wikidata":"https://www.wikidata.org/wiki/Q43015","display_name":"Finance","level":1,"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/C166957645","wikidata":"https://www.wikidata.org/wiki/Q23498","display_name":"Archaeology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/p19-1270","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1270","pdf_url":"https://www.aclweb.org/anthology/P19-1270.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/p19-1270","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/p19-1270","pdf_url":"https://www.aclweb.org/anthology/P19-1270.pdf","source":null,"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics","raw_type":"proceedings-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G1800021237","display_name":null,"funder_award_id":"1420941","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G2955745789","display_name":null,"funder_award_id":"1566382","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G3317480652","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G6157611769","display_name":"RI: Small: Collaborative Research: Computational Methods for Argument Mining: Extraction, Aggregation, and Generation","funder_award_id":"1813341","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G7033253288","display_name":null,"funder_award_id":"Grants","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"},{"id":"https://openalex.org/G848032724","display_name":null,"funder_award_id":"Science","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"},{"id":"https://openalex.org/G8934927558","display_name":null,"funder_award_id":"61877020","funder_id":"https://openalex.org/F4320321001","funder_display_name":"National Natural Science Foundation of China"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"},{"id":"https://openalex.org/F4320321001","display_name":"National Natural Science Foundation of China","ror":"https://ror.org/01h0zpd94"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2951128894.pdf","grobid_xml":"https://content.openalex.org/works/W2951128894.grobid-xml"},"referenced_works_count":24,"referenced_works":["https://openalex.org/W1025179915","https://openalex.org/W1522301498","https://openalex.org/W1654173042","https://openalex.org/W1902237438","https://openalex.org/W2048508267","https://openalex.org/W2098697179","https://openalex.org/W2111214786","https://openalex.org/W2137986939","https://openalex.org/W2139750075","https://openalex.org/W2143017621","https://openalex.org/W2156387975","https://openalex.org/W2250539671","https://openalex.org/W2470372903","https://openalex.org/W2551396370","https://openalex.org/W2605659599","https://openalex.org/W2756882086","https://openalex.org/W2779940374","https://openalex.org/W2803119452","https://openalex.org/W2951008357","https://openalex.org/W2951617294","https://openalex.org/W2953320089","https://openalex.org/W2963367922","https://openalex.org/W2963955897","https://openalex.org/W2964121744"],"related_works":["https://openalex.org/W2899084033","https://openalex.org/W1968552888","https://openalex.org/W2374116601","https://openalex.org/W3093134843","https://openalex.org/W1511346092","https://openalex.org/W1527532029","https://openalex.org/W2378167147","https://openalex.org/W3210777354","https://openalex.org/W2281307425","https://openalex.org/W2772323916"],"abstract_inverted_index":{"As":[0],"the":[1,60,63,67,102,144],"online":[2],"world":[3],"continues":[4],"its":[5],"exponential":[6],"growth,":[7],"interpersonal":[8],"communication":[9],"has":[10],"come":[11,47],"to":[12,25,49,99],"play":[13],"an":[14,135],"increasingly":[15],"central":[16],"role":[17],"in":[18,77,111],"opinion":[19],"formation":[20],"and":[21,66,95,105,124],"change.":[22],"In":[23],"order":[24],"help":[26],"users":[27],"better":[28],"engage":[29],"with":[30,86,117,132],"each":[31,90],"other":[32],"online,":[33],"we":[34,81],"study":[35],"a":[36,44,50,83],"challenging":[37],"problem":[38],"of":[39,62,138],"re-entry":[40,113],"prediction":[41],"foreseeing":[42],"whether":[43],"user":[45,93,106],"will":[46,72],"back":[48],"conversation":[51,103],"they":[52],"once":[53],"participated":[54],"in.":[55],"We":[56,115],"hypothesize":[57],"that":[58,128],"both":[59],"context":[61,104],"ongoing":[64],"conversations":[65],"users'":[68],"previous":[69,148],"chatting":[70,107],"history":[71,108],"affect":[73],"their":[74,112],"continued":[75],"interests":[76],"future":[78],"engagement.":[79],"Specifically,":[80],"propose":[82],"neural":[84],"framework":[85,131],"three":[87],"main":[88],"layers,":[89],"modeling":[91],"context,":[92],"history,":[94],"interactions":[96],"between":[97],"them,":[98],"explore":[100],"how":[101],"jointly":[109],"result":[110],"behavior.":[114],"experiment":[116],"two":[118],"large-scale":[119],"datasets":[120],"collected":[121],"from":[122,147],"Twitter":[123,141],"Reddit.":[125],"Results":[126],"show":[127],"our":[129],"proposed":[130],"biattention":[133],"achieves":[134],"F1":[136],"score":[137],"61.1":[139],"on":[140],"conversations,":[142],"outperforming":[143],"state-ofthe-art":[145],"methods":[146],"work.":[149]},"counts_by_year":[{"year":2023,"cited_by_count":2},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":6},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":1}],"updated_date":"2026-04-13T07:58:08.660418","created_date":"2025-10-10T00:00:00"}
