{"id":"https://openalex.org/W2091190355","doi":"https://doi.org/10.5220/0005170305300537","title":"Combining N-gram based Similarity Analysis with Sentiment Analysis in Web Content Classification","display_name":"Combining N-gram based Similarity Analysis with Sentiment Analysis in Web Content Classification","publication_year":2014,"publication_date":"2014-01-01","ids":{"openalex":"https://openalex.org/W2091190355","doi":"https://doi.org/10.5220/0005170305300537","mag":"2091190355"},"language":"en","primary_location":{"id":"doi:10.5220/0005170305300537","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0005170305300537","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Knowledge Discovery and Information Retrieval","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://doi.org/10.5220/0005170305300537","any_repository_has_fulltext":null},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5109309339","display_name":"Shuhua Liu","orcid":null},"institutions":[{"id":"https://openalex.org/I198445264","display_name":"Arcada University of Applied Sciences","ror":"https://ror.org/02s466x84","country_code":"FI","type":"education","lineage":["https://openalex.org/I198445264"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Shuhua Liu","raw_affiliation_strings":["Arcada University of Applied Sciences, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arcada University of Applied Sciences, Finland","institution_ids":["https://openalex.org/I198445264"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5029109348","display_name":"Thomas Forss","orcid":null},"institutions":[{"id":"https://openalex.org/I198445264","display_name":"Arcada University of Applied Sciences","ror":"https://ror.org/02s466x84","country_code":"FI","type":"education","lineage":["https://openalex.org/I198445264"]}],"countries":["FI"],"is_corresponding":false,"raw_author_name":"Thomas Forss","raw_affiliation_strings":["Arcada University of Applied Sciences, Finland"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Arcada University of Applied Sciences, Finland","institution_ids":["https://openalex.org/I198445264"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":0.8458,"has_fulltext":false,"cited_by_count":43,"citation_normalized_percentile":{"value":0.81945519,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":94,"max":99},"biblio":{"volume":null,"issue":null,"first_page":null,"last_page":null},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.9969000220298767,"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/T12262","display_name":"Hate Speech and Cyberbullying Detection","score":0.9969000220298767,"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/T11644","display_name":"Spam and Phishing Detection","score":0.9926000237464905,"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/T10664","display_name":"Sentiment Analysis and Opinion Mining","score":0.9696999788284302,"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":0.7731514573097229},{"id":"https://openalex.org/keywords/n-gram","display_name":"n-gram","score":0.6699694395065308},{"id":"https://openalex.org/keywords/similarity","display_name":"Similarity (geometry)","score":0.6241579651832581},{"id":"https://openalex.org/keywords/context","display_name":"Context (archaeology)","score":0.5508090853691101},{"id":"https://openalex.org/keywords/representation","display_name":"Representation (politics)","score":0.5165490508079529},{"id":"https://openalex.org/keywords/web-content","display_name":"Web content","score":0.4928426742553711},{"id":"https://openalex.org/keywords/content","display_name":"Content (measure theory)","score":0.49117347598075867},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.4891989231109619},{"id":"https://openalex.org/keywords/web-page","display_name":"Web page","score":0.46556520462036133},{"id":"https://openalex.org/keywords/sentiment-analysis","display_name":"Sentiment analysis","score":0.46445441246032715},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4076606035232544},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.18610545992851257},{"id":"https://openalex.org/keywords/language-model","display_name":"Language model","score":0.15500637888908386},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.10852563381195068}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7731514573097229},{"id":"https://openalex.org/C117884012","wikidata":"https://www.wikidata.org/wiki/Q94489","display_name":"n-gram","level":3,"score":0.6699694395065308},{"id":"https://openalex.org/C103278499","wikidata":"https://www.wikidata.org/wiki/Q254465","display_name":"Similarity (geometry)","level":3,"score":0.6241579651832581},{"id":"https://openalex.org/C2779343474","wikidata":"https://www.wikidata.org/wiki/Q3109175","display_name":"Context (archaeology)","level":2,"score":0.5508090853691101},{"id":"https://openalex.org/C2776359362","wikidata":"https://www.wikidata.org/wiki/Q2145286","display_name":"Representation (politics)","level":3,"score":0.5165490508079529},{"id":"https://openalex.org/C2776324614","wikidata":"https://www.wikidata.org/wiki/Q3948731","display_name":"Web content","level":3,"score":0.4928426742553711},{"id":"https://openalex.org/C2778152352","wikidata":"https://www.wikidata.org/wiki/Q5165061","display_name":"Content (measure theory)","level":2,"score":0.49117347598075867},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.4891989231109619},{"id":"https://openalex.org/C21959979","wikidata":"https://www.wikidata.org/wiki/Q36774","display_name":"Web page","level":2,"score":0.46556520462036133},{"id":"https://openalex.org/C66402592","wikidata":"https://www.wikidata.org/wiki/Q2271421","display_name":"Sentiment analysis","level":2,"score":0.46445441246032715},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4076606035232544},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.18610545992851257},{"id":"https://openalex.org/C137293760","wikidata":"https://www.wikidata.org/wiki/Q3621696","display_name":"Language model","level":2,"score":0.15500637888908386},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.10852563381195068},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C94625758","wikidata":"https://www.wikidata.org/wiki/Q7163","display_name":"Politics","level":2,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.0},{"id":"https://openalex.org/C17744445","wikidata":"https://www.wikidata.org/wiki/Q36442","display_name":"Political science","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/C151730666","wikidata":"https://www.wikidata.org/wiki/Q7205","display_name":"Paleontology","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.5220/0005170305300537","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0005170305300537","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Knowledge Discovery and Information Retrieval","raw_type":"proceedings-article"}],"best_oa_location":{"id":"doi:10.5220/0005170305300537","is_oa":true,"landing_page_url":"https://doi.org/10.5220/0005170305300537","pdf_url":null,"source":null,"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the International Conference on Knowledge Discovery and Information Retrieval","raw_type":"proceedings-article"},"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/16","score":0.5799999833106995,"display_name":"Peace, Justice and strong institutions"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":0,"referenced_works":[],"related_works":["https://openalex.org/W2548633793","https://openalex.org/W2897171874","https://openalex.org/W1987716395","https://openalex.org/W2012575882","https://openalex.org/W2544674189","https://openalex.org/W2550808318","https://openalex.org/W4346570","https://openalex.org/W2278505189","https://openalex.org/W2262826214","https://openalex.org/W2367003870"],"abstract_inverted_index":{"This":[0],"research":[1],"concerns":[2],"the":[3,69,94,140,191],"development":[4],"of":[5,36,71,126,134],"web":[6,18,37,76,164,197],"content":[7,22,57,141,165],"detection":[8,72],"systems":[9],"that":[10,33,42,96,119,147,176],"will":[11],"be":[12],"able":[13],"to":[14,50,110],"automatically":[15],"classify":[16,51],"any":[17],"page":[19],"into":[20,64,79,88],"pre-defined":[21],"categories.":[23,198],"Our":[24,144],"work":[25],"is":[26],"motivated":[27],"by":[28],"practical":[29],"experience":[30],"and":[31,45,58,106,161,193],"observations":[32],"certain":[34],"categories":[35],"pages,":[38],"such":[39],"as":[40],"those":[41],"contain":[43],"hatred":[44],"violence,":[46],"are":[47,61],"much":[48,154],"harder":[49],"with":[52,181],"good":[53],"accuracy":[54],"when":[55],"both":[56],"structural":[59],"features":[60,78,180],"already":[62],"taken":[63],"account.":[65],"To":[66],"further":[67],"improve":[68],"performance":[70],"systems,":[73],"we":[74,84,131],"bring":[75,184],"sentiment":[77,182],"classification":[80,90,142],"models.":[81,143],"In":[82],"addition,":[83],"incorporate":[85],"n-gram":[86,169],"representation":[87],"our":[89],"approach,":[91,156],"based":[92,149,170,174],"on":[93],"assumption":[95],"n-grams":[97,127,137],"can":[98],"capture":[99],"more":[100],"local":[101],"context":[102],"information":[103],"in":[104,128,138,163,187],"text,":[105],"thus":[107],"could":[108],"help":[109],"enhance":[111],"topic":[112,178],"similarity":[113,179],"analysis.":[114],"Different":[115],"from":[116],"most":[117],"studies":[118],"only":[120],"consider":[121],"presence":[122],"or":[123],"frequency":[124],"count":[125],"their":[129,158],"applications,":[130],"make":[132],"use":[133],"tf-idf":[135],"weighted":[136],"building":[139],"result":[145],"shows":[146],"unigram":[148],"models,":[150],"even":[151],"though":[152],"a":[153],"simpler":[155],"show":[157],"unique":[159],"value":[160],"effectiveness":[162],"classification.":[166],"Higher":[167],"order":[168],"approaches,":[171],"especially":[172],"5-gram":[173],"models":[175],"combine":[177],"features,":[183],"significant":[185],"improvement":[186],"precision":[188],"levels":[189],"for":[190],"Violence":[192],"two":[194],"Racism":[195],"related":[196]},"counts_by_year":[{"year":2025,"cited_by_count":4},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":8},{"year":2022,"cited_by_count":6},{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":3},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":12},{"year":2015,"cited_by_count":2}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2025-10-10T00:00:00"}