{"id":"https://openalex.org/W2914424054","doi":"https://doi.org/10.1109/bigdata.2018.8622319","title":"Longitudinal Analysis of Linguistic flexibility of Value-motivated Groups","display_name":"Longitudinal Analysis of Linguistic flexibility of Value-motivated Groups","publication_year":2018,"publication_date":"2018-12-01","ids":{"openalex":"https://openalex.org/W2914424054","doi":"https://doi.org/10.1109/bigdata.2018.8622319","mag":"2914424054"},"language":"en","primary_location":{"id":"doi:10.1109/bigdata.2018.8622319","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622319","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","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/A5062232172","display_name":"Mohammad Al Boni","orcid":null},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Mohammad Al Boni","raw_affiliation_strings":["Data Science Institute, University of Virginia, Virginia, United States"],"affiliations":[{"raw_affiliation_string":"Data Science Institute, University of Virginia, Virginia, United States","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5011356074","display_name":"Seth Green","orcid":null},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Seth Green","raw_affiliation_strings":["Data Science Institute, University of Virginia, Virginia, United States"],"affiliations":[{"raw_affiliation_string":"Data Science Institute, University of Virginia, Virginia, United States","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5009477824","display_name":"M.E. Stiles","orcid":null},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Megan Stiles","raw_affiliation_strings":["Data Science Institute, University of Virginia, Virginia, United States"],"affiliations":[{"raw_affiliation_string":"Data Science Institute, University of Virginia, Virginia, United States","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5026012812","display_name":"Katherine Harton","orcid":null},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Katherine Harton","raw_affiliation_strings":["Data Science Institute, University of Virginia, Virginia, United States"],"affiliations":[{"raw_affiliation_string":"Data Science Institute, University of Virginia, Virginia, United States","institution_ids":["https://openalex.org/I51556381"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5086462231","display_name":"Donald E. Brown","orcid":"https://orcid.org/0000-0002-9140-2632"},"institutions":[{"id":"https://openalex.org/I51556381","display_name":"University of Virginia","ror":"https://ror.org/0153tk833","country_code":"US","type":"education","lineage":["https://openalex.org/I51556381"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Donald E. Brown","raw_affiliation_strings":["Data Science Institute, University of Virginia, Virginia, United States"],"affiliations":[{"raw_affiliation_string":"Data Science Institute, University of Virginia, Virginia, United States","institution_ids":["https://openalex.org/I51556381"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":5,"corresponding_author_ids":["https://openalex.org/A5062232172"],"corresponding_institution_ids":["https://openalex.org/I51556381"],"apc_list":null,"apc_paid":null,"fwci":0.0,"has_fulltext":false,"cited_by_count":0,"citation_normalized_percentile":{"value":0.19659295,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"2","issue":null,"first_page":"2951","last_page":"2959"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10064","display_name":"Complex Network Analysis Techniques","score":0.9894000291824341,"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":0.9894000291824341,"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/T12592","display_name":"Opinion Dynamics and Social Influence","score":0.9871000051498413,"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/T10557","display_name":"Social Media and Politics","score":0.9861999750137329,"subfield":{"id":"https://openalex.org/subfields/3315","display_name":"Communication"},"field":{"id":"https://openalex.org/fields/33","display_name":"Social Sciences"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/weighting","display_name":"Weighting","score":0.6588375568389893},{"id":"https://openalex.org/keywords/premise","display_name":"Premise","score":0.6277533173561096},{"id":"https://openalex.org/keywords/flexibility","display_name":"Flexibility (engineering)","score":0.6150987148284912},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.5934404134750366},{"id":"https://openalex.org/keywords/value","display_name":"Value (mathematics)","score":0.5225576758384705},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.440416157245636},{"id":"https://openalex.org/keywords/performative-utterance","display_name":"Performative utterance","score":0.43300577998161316},{"id":"https://openalex.org/keywords/pragmatics","display_name":"Pragmatics","score":0.41309767961502075},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.39933666586875916},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.3537028431892395},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.24487262964248657},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.2347734570503235},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.19874367117881775}],"concepts":[{"id":"https://openalex.org/C183115368","wikidata":"https://www.wikidata.org/wiki/Q856577","display_name":"Weighting","level":2,"score":0.6588375568389893},{"id":"https://openalex.org/C2778023277","wikidata":"https://www.wikidata.org/wiki/Q321703","display_name":"Premise","level":2,"score":0.6277533173561096},{"id":"https://openalex.org/C2780598303","wikidata":"https://www.wikidata.org/wiki/Q65921492","display_name":"Flexibility (engineering)","level":2,"score":0.6150987148284912},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.5934404134750366},{"id":"https://openalex.org/C2776291640","wikidata":"https://www.wikidata.org/wiki/Q2912517","display_name":"Value (mathematics)","level":2,"score":0.5225576758384705},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.440416157245636},{"id":"https://openalex.org/C134141054","wikidata":"https://www.wikidata.org/wiki/Q965415","display_name":"Performative utterance","level":2,"score":0.43300577998161316},{"id":"https://openalex.org/C11693617","wikidata":"https://www.wikidata.org/wiki/Q181839","display_name":"Pragmatics","level":2,"score":0.41309767961502075},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.39933666586875916},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.3537028431892395},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.24487262964248657},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.2347734570503235},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.19874367117881775},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0},{"id":"https://openalex.org/C126838900","wikidata":"https://www.wikidata.org/wiki/Q77604","display_name":"Radiology","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:10.1109/bigdata.2018.8622319","is_oa":false,"landing_page_url":"https://doi.org/10.1109/bigdata.2018.8622319","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2018 IEEE International Conference on Big Data (Big Data)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","display_name":"Peace, Justice and strong institutions","score":0.6800000071525574}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":26,"referenced_works":["https://openalex.org/W273955616","https://openalex.org/W658020064","https://openalex.org/W1989942403","https://openalex.org/W1993318811","https://openalex.org/W2048616366","https://openalex.org/W2063395966","https://openalex.org/W2070910370","https://openalex.org/W2080404274","https://openalex.org/W2089125183","https://openalex.org/W2135695572","https://openalex.org/W2137226992","https://openalex.org/W2153579005","https://openalex.org/W2160660844","https://openalex.org/W2250539671","https://openalex.org/W2419919282","https://openalex.org/W2435251607","https://openalex.org/W2461642619","https://openalex.org/W2621177716","https://openalex.org/W4213009331","https://openalex.org/W4249454004","https://openalex.org/W4294170691","https://openalex.org/W6610017368","https://openalex.org/W6621906925","https://openalex.org/W6680532697","https://openalex.org/W6682691769","https://openalex.org/W6717827561"],"related_works":["https://openalex.org/W590788508","https://openalex.org/W1593975901","https://openalex.org/W2611974471","https://openalex.org/W4313233093","https://openalex.org/W2358082531","https://openalex.org/W2589976903","https://openalex.org/W4200481647","https://openalex.org/W2074460591","https://openalex.org/W2595902454","https://openalex.org/W2890981035"],"abstract_inverted_index":{"Increasing":[0],"globalization":[1],"of":[2,52,61,75,127,141,168,185,223,236],"the":[3,50,100,125,166,176,182,198,221,233],"world":[4],"leads":[5],"to":[6,12,30,48,130,147,175,181,232],"an":[7],"emerging":[8],"need":[9],"for":[10,86,154,193,246],"ways":[11],"analysis":[13,44],"and":[14,20,34,72,77,108,143,226,229],"understand":[15],"groups":[16,54,110],"from":[17,55],"different":[18,224],"cultures":[19],"ideologies.":[21],"Researchers":[22],"have":[23,104],"used":[24,146],"written":[25],"text":[26,66,97],"as":[27,115],"a":[28,161,169,172,190,204,210,241],"medium":[29],"examine":[31],"political":[32],"discourse":[33],"analyze":[35,124],"value-motivated":[36,53,109],"groups.":[37,101,237],"Previous":[38],"works":[39,63,82],"showed":[40],"that":[41,65,106,136,160,203],"computational":[42],"linguistic":[43,225,234],"can":[45,67],"be":[46,112],"performed":[47],"infer":[49],"flexibility":[51,150,235],"their":[56,93,230],"writings.":[57],"The":[58],"main":[59],"premise":[60],"these":[62],"is":[64],"bring":[68],"insights":[69,219],"into":[70,220],"individuals'":[71],"groups'":[73,88,149],"way":[74],"thinking,":[76],"potentially,":[78],"behaviour.":[79],"While":[80],"existing":[81,128],"provide":[83],"viable":[84],"solutions":[85],"characterizing":[87],"ideological":[89],"behaviour,":[90],"they":[91,116],"perform":[92],"analyses":[94],"over":[95],"all":[96],"published":[98],"by":[99,249],"However,":[102],"researchers":[103],"found":[105],"religious":[107],"can't":[111],"analyzed":[113],"collectively":[114],"regularly":[117],"evolve.":[118],"To":[119],"address":[120],"this":[121],"gap,":[122],"we":[123,188],"performance":[126],"methods":[129],"single":[131,155],"documents.":[132],"Experimental":[133],"results":[134],"show":[135,159],"previous":[137],"features":[138],"(e.g.,":[139],"use":[140,248],"pronouns":[142],"judgment":[144],"statements)":[145],"predict":[148],"are":[151],"less":[152],"predictive":[153],"documents'":[156],"flexibility.":[157],"We":[158],"newly":[162],"added":[163],"feature":[164],"regarding":[165],"identity":[167],"group":[170],"provides":[171,240],"significant":[173],"contribution":[174],"prediction":[177],"process.":[178],"Furthermore,":[179],"due":[180],"unbalanced":[183],"nature":[184],"our":[186],"data,":[187],"propose":[189],"weighting":[191],"scheme":[192],"linear":[194],"regression":[195],"based":[196],"on":[197],"inter-group":[199],"variance.":[200],"Results":[201],"indicate":[202],"weighted":[205],"least":[206,212],"squares":[207,213],"significantly":[208],"outperforms":[209],"traditional":[211],"approach.":[214],"This":[215],"work":[216],"brings":[217],"new":[218],"characteristics":[222],"performative":[227],"signals,":[228],"relationship":[231],"It":[238],"also":[239],"decision":[242],"making":[243],"support":[244],"tool":[245],"practical":[247],"practitioners.":[250]},"counts_by_year":[],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}