{"id":"https://openalex.org/W3176370143","doi":"https://doi.org/10.1109/icccsp52374.2021.9465497","title":"ArtiMarker: A Novel Artificially Inflated Video Marking And Characterization Method on YouTube","display_name":"ArtiMarker: A Novel Artificially Inflated Video Marking And Characterization Method on YouTube","publication_year":2021,"publication_date":"2021-05-24","ids":{"openalex":"https://openalex.org/W3176370143","doi":"https://doi.org/10.1109/icccsp52374.2021.9465497","mag":"3176370143"},"language":"en","primary_location":{"id":"doi:10.1109/icccsp52374.2021.9465497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccsp52374.2021.9465497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 5th International Conference on Computer, Communication and Signal Processing (ICCCSP)","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/A5055783149","display_name":"Deepika Varshney","orcid":"https://orcid.org/0000-0002-9728-0525"},"institutions":[{"id":"https://openalex.org/I863896202","display_name":"Delhi Technological University","ror":"https://ror.org/01ztcvt22","country_code":"IN","type":"education","lineage":["https://openalex.org/I863896202"]}],"countries":["IN"],"is_corresponding":true,"raw_author_name":"Deepika Varshney","raw_affiliation_strings":["Delhi Technological University, Delhi, India"],"affiliations":[{"raw_affiliation_string":"Delhi Technological University, Delhi, India","institution_ids":["https://openalex.org/I863896202"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5066816551","display_name":"Dinesh Kumar Vishwakarma","orcid":"https://orcid.org/0000-0002-2421-6995"},"institutions":[{"id":"https://openalex.org/I863896202","display_name":"Delhi Technological University","ror":"https://ror.org/01ztcvt22","country_code":"IN","type":"education","lineage":["https://openalex.org/I863896202"]}],"countries":["IN"],"is_corresponding":false,"raw_author_name":"Dinesh Kumar Vishwakarma","raw_affiliation_strings":["Delhi Technological University, Delhi, India"],"affiliations":[{"raw_affiliation_string":"Delhi Technological University, Delhi, India","institution_ids":["https://openalex.org/I863896202"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5055783149"],"corresponding_institution_ids":["https://openalex.org/I863896202"],"apc_list":null,"apc_paid":null,"fwci":0.5508,"has_fulltext":false,"cited_by_count":2,"citation_normalized_percentile":{"value":0.71827711,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":94},"biblio":{"volume":null,"issue":null,"first_page":"244","last_page":"249"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9997000098228455,"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":0.9997000098228455,"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/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9988999962806702,"subfield":{"id":"https://openalex.org/subfields/1711","display_name":"Signal Processing"},"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":0.9983999729156494,"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/computer-science","display_name":"Computer science","score":0.8327192068099976},{"id":"https://openalex.org/keywords/c4.5-algorithm","display_name":"C4.5 algorithm","score":0.8085094690322876},{"id":"https://openalex.org/keywords/naive-bayes-classifier","display_name":"Naive Bayes classifier","score":0.711250364780426},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.5868239402770996},{"id":"https://openalex.org/keywords/popularity","display_name":"Popularity","score":0.5668204426765442},{"id":"https://openalex.org/keywords/decision-tree","display_name":"Decision tree","score":0.4818233549594879},{"id":"https://openalex.org/keywords/classifier","display_name":"Classifier (UML)","score":0.4496940076351166},{"id":"https://openalex.org/keywords/revenue","display_name":"Revenue","score":0.4350038468837738},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.4235777258872986},{"id":"https://openalex.org/keywords/tree","display_name":"Tree (set theory)","score":0.4121428430080414},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.37818634510040283},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.32429665327072144},{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.149338036775589}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8327192068099976},{"id":"https://openalex.org/C52003472","wikidata":"https://www.wikidata.org/wiki/Q1022655","display_name":"C4.5 algorithm","level":4,"score":0.8085094690322876},{"id":"https://openalex.org/C52001869","wikidata":"https://www.wikidata.org/wiki/Q812530","display_name":"Naive Bayes classifier","level":3,"score":0.711250364780426},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.5868239402770996},{"id":"https://openalex.org/C2780586970","wikidata":"https://www.wikidata.org/wiki/Q1357284","display_name":"Popularity","level":2,"score":0.5668204426765442},{"id":"https://openalex.org/C84525736","wikidata":"https://www.wikidata.org/wiki/Q831366","display_name":"Decision tree","level":2,"score":0.4818233549594879},{"id":"https://openalex.org/C95623464","wikidata":"https://www.wikidata.org/wiki/Q1096149","display_name":"Classifier (UML)","level":2,"score":0.4496940076351166},{"id":"https://openalex.org/C195487862","wikidata":"https://www.wikidata.org/wiki/Q850210","display_name":"Revenue","level":2,"score":0.4350038468837738},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.4235777258872986},{"id":"https://openalex.org/C113174947","wikidata":"https://www.wikidata.org/wiki/Q2859736","display_name":"Tree (set theory)","level":2,"score":0.4121428430080414},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.37818634510040283},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.32429665327072144},{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.149338036775589},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C77805123","wikidata":"https://www.wikidata.org/wiki/Q161272","display_name":"Social psychology","level":1,"score":0.0},{"id":"https://openalex.org/C15744967","wikidata":"https://www.wikidata.org/wiki/Q9418","display_name":"Psychology","level":0,"score":0.0},{"id":"https://openalex.org/C121955636","wikidata":"https://www.wikidata.org/wiki/Q4116214","display_name":"Accounting","level":1,"score":0.0},{"id":"https://openalex.org/C144133560","wikidata":"https://www.wikidata.org/wiki/Q4830453","display_name":"Business","level":0,"score":0.0},{"id":"https://openalex.org/C59822182","wikidata":"https://www.wikidata.org/wiki/Q441","display_name":"Botany","level":1,"score":0.0},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.0},{"id":"https://openalex.org/C134306372","wikidata":"https://www.wikidata.org/wiki/Q7754","display_name":"Mathematical analysis","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/icccsp52374.2021.9465497","is_oa":false,"landing_page_url":"https://doi.org/10.1109/icccsp52374.2021.9465497","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2021 5th International Conference on Computer, Communication and Signal Processing (ICCCSP)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":31,"referenced_works":["https://openalex.org/W1483048869","https://openalex.org/W1538449501","https://openalex.org/W1596850266","https://openalex.org/W1602011302","https://openalex.org/W1911162795","https://openalex.org/W1999230823","https://openalex.org/W2033076167","https://openalex.org/W2080330461","https://openalex.org/W2085533912","https://openalex.org/W2094551647","https://openalex.org/W2094871756","https://openalex.org/W2109885200","https://openalex.org/W2140519269","https://openalex.org/W2144936818","https://openalex.org/W2157579260","https://openalex.org/W2168508162","https://openalex.org/W2618571414","https://openalex.org/W2798611956","https://openalex.org/W2801504084","https://openalex.org/W2805150911","https://openalex.org/W2806879796","https://openalex.org/W2951841515","https://openalex.org/W3120575766","https://openalex.org/W4239856175","https://openalex.org/W4241915340","https://openalex.org/W6609998551","https://openalex.org/W6628650364","https://openalex.org/W6632076716","https://openalex.org/W6684716366","https://openalex.org/W6750745630","https://openalex.org/W6788175032"],"related_works":["https://openalex.org/W2997511728","https://openalex.org/W4367336074","https://openalex.org/W4214653893","https://openalex.org/W3154045278","https://openalex.org/W4379620016","https://openalex.org/W4214491888","https://openalex.org/W2149097950","https://openalex.org/W4393666307","https://openalex.org/W3210764983","https://openalex.org/W4393443811"],"abstract_inverted_index":{"YouTube":[0,81],"is":[1,34,44,133,148,178],"on":[2,80,83,126,150],"demand":[3],"platform,":[4],"crowd":[5],"sourced":[6],"by":[7],"design":[8],"and":[9,56,76,104,135,145,167],"its":[10],"huge":[11],"popularity":[12],"encourages":[13],"users":[14],"to":[15,19,37,50,57,96,102],"adopt":[16],"fraudulent":[17],"methods":[18],"inflate":[20],"viewcounts":[21],"of":[22,29,46,121,130],"their":[23],"videos,":[24,123],"thereby":[25],"increasing":[26],"the":[27,30,47,91,151,156],"revenue":[28],"video":[31,74],"uploader.":[32],"It":[33,160],"very":[35],"important":[36],"mark":[38,103],"artificially":[39,72,106],"inflated":[40,73,107],"videos":[41],"as":[42,141],"it":[43],"one":[45],"stepping":[48],"stone":[49],"encourage":[51],"false":[52],"information":[53],"over":[54],"web":[55],"gain":[58],"monetary":[59],"benefits.To":[60],"address":[61],"this":[62,65,113],"issue,":[63],"in":[64,90,112,119],"paper":[66,92,114],"we":[67],"present":[68],"\"ArtiMarker\"":[69],"a":[70,98],"novel":[71],"marking":[75],"characterization":[77],"(less,medium,high)":[78],"method":[79,101],"based":[82,149],"user":[84],"level":[85],"feature.The":[86],"proposed":[87,110,131],"technique":[88],"described":[89],"will":[93],"help":[94],"researchers":[95],"understand":[97],"new":[99],"efficient":[100],"characterize":[105],"videos.":[108],"The":[109,128],"parameters":[111],"can":[115],"also":[116],"be":[117],"used":[118],"identification":[120],"spam":[122],"fake":[124],"profiles":[125],"YouTube.":[127],"performance":[129],"work":[132],"analyzed":[134],"demonstrated":[136],"using":[137],"various":[138],"classifier":[139],"such":[140],"Decision":[142],"Tree,":[143],"Function-Based":[144],"Bayes.The":[146],"comparison":[147],"testing":[152],"strategy":[153],"utilized":[154],"during":[155],"experiments;percentage":[157],"split,cross":[158],"validation.":[159],"has":[161],"been":[162],"observed":[163],"that":[164],"Bayes":[165],"network,J48":[166],"Random":[168,176],"Forest":[169,177],"are":[170],"best":[171],"suited":[172,180],"for":[173,181],"percentage-split":[174],"while":[175],"more":[179],"cross":[182],"validation":[183],"schemes.":[184]},"counts_by_year":[{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}
