{"id":"https://openalex.org/W2739672440","doi":"https://doi.org/10.18653/v1/w17-2909","title":"Non-lexical Features Encode Political Affiliation on Twitter","display_name":"Non-lexical Features Encode Political Affiliation on Twitter","publication_year":2017,"publication_date":"2017-01-01","ids":{"openalex":"https://openalex.org/W2739672440","doi":"https://doi.org/10.18653/v1/w17-2909","mag":"2739672440"},"language":"en","primary_location":{"id":"doi:10.18653/v1/w17-2909","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-2909","pdf_url":"https://www.aclweb.org/anthology/W17-2909.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 Second Workshop on NLP and Computational Social Science","raw_type":"proceedings-article"},"type":"conference-paper","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.aclweb.org/anthology/W17-2909.pdf","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5010348114","display_name":"Rachael Tatman","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Rachael Tatman","raw_affiliation_strings":["University of Washington Linguistics Department"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington Linguistics Department","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5062957860","display_name":"Leo G Stewart","orcid":null},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Leo Stewart","raw_affiliation_strings":["University of Washington Human Centered Design Engineering"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington Human Centered Design Engineering","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5020738607","display_name":"Amandalynne Paullada","orcid":"https://orcid.org/0000-0002-9585-0125"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Amandalynne Paullada","raw_affiliation_strings":["University of Washington Linguistics Department"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington Linguistics Department","institution_ids":["https://openalex.org/I201448701"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5053945884","display_name":"Emma S. Spiro","orcid":"https://orcid.org/0000-0002-6792-3390"},"institutions":[{"id":"https://openalex.org/I201448701","display_name":"University of Washington","ror":"https://ror.org/00cvxb145","country_code":"US","type":"education","lineage":["https://openalex.org/I201448701"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Emma Spiro","raw_affiliation_strings":["University of Washington Information School Department of Sociology"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Washington Information School Department of Sociology","institution_ids":["https://openalex.org/I201448701"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":1,"corresponding_author_ids":[],"corresponding_institution_ids":["https://openalex.org/I201448701"],"apc_list":null,"apc_paid":null,"fwci":0.6921,"has_fulltext":true,"cited_by_count":10,"citation_normalized_percentile":{"value":0.74221341,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":91,"max":97},"biblio":{"volume":null,"issue":null,"first_page":"63","last_page":"67"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12380","display_name":"Authorship Attribution and Profiling","score":0.9988999962806702,"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/T12380","display_name":"Authorship Attribution and Profiling","score":0.9988999962806702,"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.9973000288009644,"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/T10557","display_name":"Social Media and Politics","score":0.9959999918937683,"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/punctuation","display_name":"Punctuation","score":0.8403613567352295},{"id":"https://openalex.org/keywords/encode","display_name":"ENCODE","score":0.7193052172660828},{"id":"https://openalex.org/keywords/politics","display_name":"Politics","score":0.689953088760376},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6143221259117126},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.5766891241073608},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4857766926288605},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4768839180469513},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.46879228949546814},{"id":"https://openalex.org/keywords/capitalization","display_name":"Capitalization","score":0.45974212884902954},{"id":"https://openalex.org/keywords/linguistics","display_name":"Linguistics","score":0.4048210680484772},{"id":"https://openalex.org/keywords/political-science","display_name":"Political science","score":0.2419201135635376}],"concepts":[{"id":"https://openalex.org/C540372491","wikidata":"https://www.wikidata.org/wiki/Q82622","display_name":"Punctuation","level":2,"score":0.8403613567352295},{"id":"https://openalex.org/C66746571","wikidata":"https://www.wikidata.org/wiki/Q1134833","display_name":"ENCODE","level":3,"score":0.7193052172660828},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.689953088760376},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6143221259117126},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.5766891241073608},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4857766926288605},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4768839180469513},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.46879228949546814},{"id":"https://openalex.org/C2779137862","wikidata":"https://www.wikidata.org/wiki/Q425951","display_name":"Capitalization","level":2,"score":0.45974212884902954},{"id":"https://openalex.org/C41895202","wikidata":"https://www.wikidata.org/wiki/Q8162","display_name":"Linguistics","level":1,"score":0.4048210680484772},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","level":0,"score":0.2419201135635376},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C199539241","wikidata":"https://www.wikidata.org/wiki/Q7748","display_name":"Law","level":1,"score":0.0},{"id":"https://openalex.org/C138885662","wikidata":"https://www.wikidata.org/wiki/Q5891","display_name":"Philosophy","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.18653/v1/w17-2909","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-2909","pdf_url":"https://www.aclweb.org/anthology/W17-2909.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 Second Workshop on NLP and Computational Social Science","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.18653/v1/w17-2909","is_oa":true,"landing_page_url":"https://doi.org/10.18653/v1/w17-2909","pdf_url":"https://www.aclweb.org/anthology/W17-2909.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 Second Workshop on NLP and Computational Social Science","raw_type":"proceedings-article"},"sustainable_development_goals":[{"display_name":"Reduced inequalities","score":0.6899999976158142,"id":"https://metadata.un.org/sdg/10"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W2739672440.pdf","grobid_xml":"https://content.openalex.org/works/W2739672440.grobid-xml"},"referenced_works_count":22,"referenced_works":["https://openalex.org/W68298479","https://openalex.org/W100648375","https://openalex.org/W326142932","https://openalex.org/W1458448385","https://openalex.org/W1513618424","https://openalex.org/W2106895453","https://openalex.org/W2107772748","https://openalex.org/W2125910575","https://openalex.org/W2151518054","https://openalex.org/W2158295279","https://openalex.org/W2165281381","https://openalex.org/W2255452591","https://openalex.org/W2342270822","https://openalex.org/W2397481274","https://openalex.org/W2489406233","https://openalex.org/W2532755691","https://openalex.org/W2538660910","https://openalex.org/W2604110998","https://openalex.org/W2606131891","https://openalex.org/W2915177913","https://openalex.org/W3017658320","https://openalex.org/W4399438375"],"related_works":["https://openalex.org/W3105168542","https://openalex.org/W3041481294","https://openalex.org/W2901590103","https://openalex.org/W3094774238","https://openalex.org/W2167662847","https://openalex.org/W38394648","https://openalex.org/W4312833533","https://openalex.org/W4317655900","https://openalex.org/W2800016038","https://openalex.org/W3015597294"],"abstract_inverted_index":{"Previous":[0],"work":[1],"on":[2,11],"classifying":[3],"Twitter":[4],"users'":[5,34],"political":[6,22],"alignment":[7],"has":[8],"mainly":[9],"focused":[10],"lexical":[12],"and":[13,45,52,68],"social":[14],"network":[15],"features.":[16],"This":[17],"study":[18],"provides":[19],"evidence":[20],"that":[21,40],"affiliation":[23],"is":[24],"also":[25],"reflected":[26],"in":[27],"features":[28],"which":[29],"have":[30],"been":[31],"previously":[32],"overlooked:":[33],"discourse":[35,67],"patterns":[36],"(proportion":[37],"of":[38,48,50],"Tweets":[39],"are":[41,73],"retweets":[42],"or":[43],"replies)":[44],"their":[46],"rate":[47],"use":[49],"capitalization":[51],"punctuation.":[53],"We":[54],"find":[55],"robust":[56],"differences":[57],"between":[58],"politically":[59],"left-and":[60],"right-leaning":[61],"communities":[62],"with":[63],"respect":[64],"to":[65,76],"these":[66],"sub-lexical":[69],"features,":[70],"although":[71],"they":[72],"not":[74],"enough":[75],"train":[77],"a":[78],"high-accuracy":[79],"classifier.":[80]},"counts_by_year":[{"year":2025,"cited_by_count":1},{"year":2022,"cited_by_count":2},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":2},{"year":2018,"cited_by_count":3}],"updated_date":"2026-07-29T14:22:42.915294","created_date":"2025-10-10T00:00:00"}