{"id":"https://openalex.org/W2769951052","doi":"https://doi.org/10.1145/3110025.3110163","title":"BotWalk","display_name":"BotWalk","publication_year":2017,"publication_date":"2017-07-31","ids":{"openalex":"https://openalex.org/W2769951052","doi":"https://doi.org/10.1145/3110025.3110163","mag":"2769951052"},"language":"en","primary_location":{"id":"doi:10.1145/3110025.3110163","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3110025.3110163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017","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/A5003684324","display_name":"Amanda Minnich","orcid":"https://orcid.org/0000-0001-8191-5322"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Amanda Minnich","raw_affiliation_strings":["University of New Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of New Mexico","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5021319189","display_name":"Nikan Chavoshi","orcid":null},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Nikan Chavoshi","raw_affiliation_strings":["University of New Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of New Mexico","institution_ids":[]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5015996266","display_name":"Danai Koutra","orcid":"https://orcid.org/0000-0002-3206-8179"},"institutions":[{"id":"https://openalex.org/I27837315","display_name":"University of Michigan","ror":"https://ror.org/00jmfr291","country_code":"US","type":"education","lineage":["https://openalex.org/I27837315"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Danai Koutra","raw_affiliation_strings":["University of Michigan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of Michigan","institution_ids":["https://openalex.org/I27837315"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5025138797","display_name":"Abdullah Mueen","orcid":"https://orcid.org/0000-0002-4839-1624"},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Abdullah Mueen","raw_affiliation_strings":["University of New Mexico"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"University of New Mexico","institution_ids":[]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":12.66,"has_fulltext":false,"cited_by_count":59,"citation_normalized_percentile":{"value":0.98587397,"is_in_top_1_percent":false,"is_in_top_10_percent":true},"cited_by_percentile_year":{"min":95,"max":99},"biblio":{"volume":null,"issue":null,"first_page":"467","last_page":"474"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":0.9998000264167786,"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":0.9998000264167786,"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/T10400","display_name":"Network Security and Intrusion Detection","score":0.9997000098228455,"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"}},{"id":"https://openalex.org/T11241","display_name":"Advanced Malware Detection Techniques","score":0.9984999895095825,"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"}}],"keywords":[{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.8007428646087646},{"id":"https://openalex.org/keywords/metadata","display_name":"Metadata","score":0.6377299427986145},{"id":"https://openalex.org/keywords/anomaly-detection","display_name":"Anomaly detection","score":0.5450740456581116},{"id":"https://openalex.org/keywords/feature-vector","display_name":"Feature vector","score":0.5027608871459961},{"id":"https://openalex.org/keywords/feature-extraction","display_name":"Feature extraction","score":0.502713680267334},{"id":"https://openalex.org/keywords/process","display_name":"Process (computing)","score":0.47200489044189453},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.47176459431648254},{"id":"https://openalex.org/keywords/identification","display_name":"Identification (biology)","score":0.45523905754089355},{"id":"https://openalex.org/keywords/isolation","display_name":"Isolation (microbiology)","score":0.43768197298049927},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.41150620579719543},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.3868602514266968},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.32812437415122986},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.14657875895500183}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8007428646087646},{"id":"https://openalex.org/C93518851","wikidata":"https://www.wikidata.org/wiki/Q180160","display_name":"Metadata","level":2,"score":0.6377299427986145},{"id":"https://openalex.org/C739882","wikidata":"https://www.wikidata.org/wiki/Q3560506","display_name":"Anomaly detection","level":2,"score":0.5450740456581116},{"id":"https://openalex.org/C83665646","wikidata":"https://www.wikidata.org/wiki/Q42139305","display_name":"Feature vector","level":2,"score":0.5027608871459961},{"id":"https://openalex.org/C52622490","wikidata":"https://www.wikidata.org/wiki/Q1026626","display_name":"Feature extraction","level":2,"score":0.502713680267334},{"id":"https://openalex.org/C98045186","wikidata":"https://www.wikidata.org/wiki/Q205663","display_name":"Process (computing)","level":2,"score":0.47200489044189453},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.47176459431648254},{"id":"https://openalex.org/C116834253","wikidata":"https://www.wikidata.org/wiki/Q2039217","display_name":"Identification (biology)","level":2,"score":0.45523905754089355},{"id":"https://openalex.org/C2775941552","wikidata":"https://www.wikidata.org/wiki/Q25212305","display_name":"Isolation (microbiology)","level":2,"score":0.43768197298049927},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.41150620579719543},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.3868602514266968},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.32812437415122986},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.14657875895500183},{"id":"https://openalex.org/C111919701","wikidata":"https://www.wikidata.org/wiki/Q9135","display_name":"Operating system","level":1,"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/C89423630","wikidata":"https://www.wikidata.org/wiki/Q7193","display_name":"Microbiology","level":1,"score":0.0},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1145/3110025.3110163","is_oa":false,"landing_page_url":"https://doi.org/10.1145/3110025.3110163","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Proceedings of the 2017 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining 2017","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G763866905","display_name":null,"funder_award_id":"DGE-0237002","funder_id":"https://openalex.org/F4320306076","funder_display_name":"National Science Foundation"}],"funders":[{"id":"https://openalex.org/F4320306076","display_name":"National Science Foundation","ror":"https://ror.org/021nxhr62"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":32,"referenced_works":["https://openalex.org/W9223698","https://openalex.org/W84853486","https://openalex.org/W164607750","https://openalex.org/W611119698","https://openalex.org/W746997338","https://openalex.org/W1517059634","https://openalex.org/W1568955415","https://openalex.org/W1600782690","https://openalex.org/W1672660286","https://openalex.org/W1815362064","https://openalex.org/W1929765742","https://openalex.org/W1946579785","https://openalex.org/W2020264290","https://openalex.org/W2072715695","https://openalex.org/W2108601876","https://openalex.org/W2144182447","https://openalex.org/W2186741084","https://openalex.org/W2212259974","https://openalex.org/W2238500808","https://openalex.org/W2249382963","https://openalex.org/W2263846226","https://openalex.org/W2278635123","https://openalex.org/W2296719434","https://openalex.org/W2405326156","https://openalex.org/W2535218596","https://openalex.org/W2583516892","https://openalex.org/W2612367592","https://openalex.org/W3098249847","https://openalex.org/W4254182148","https://openalex.org/W4300013312","https://openalex.org/W6694650807","https://openalex.org/W6737079845"],"related_works":["https://openalex.org/W2058118494","https://openalex.org/W2392768766","https://openalex.org/W2382021449","https://openalex.org/W2095118173","https://openalex.org/W2106424170","https://openalex.org/W1985426483","https://openalex.org/W2501188010","https://openalex.org/W4299935056","https://openalex.org/W2010935248","https://openalex.org/W2768810474"],"abstract_inverted_index":{"We":[0,45,60,80],"propose":[1],"BotWalk,":[2],"a":[3,64,82,156,169,176],"near-real":[4],"time":[5],"adaptive":[6],"Twitter":[7,20,100],"exploration":[8],"algorithm":[9],"to":[10,17,27,33,54,139,162],"identify":[11,41,55,81,141],"bots":[12,21,56,119,155,167,174],"exhibiting":[13],"novel":[14,42,142],"behavior.":[15,144],"Due":[16],"suspension":[18],"pressure,":[19],"are":[22,36,120],"constantly":[23],"changing":[24],"their":[25],"behavior":[26],"evade":[28],"detection.":[29],"Traditional":[30],"supervised":[31],"approaches":[32],"bot":[34,43,84,143],"detection":[35,110],"non-adaptive":[37],"and":[38,77,104,126],"thus":[39],"cannot":[40],"behaviors.":[44],"therefore":[46],"devise":[47],"an":[48,106],"unsupervised":[49,107],"approach,":[50],"which":[51,68],"allows":[52,146],"us":[53,138,161],"as":[57],"they":[58],"evolve.":[59],"characterize":[61],"users":[62],"with":[63,132,175],"behavioral":[65,115],"feature":[66],"vector":[67],"consists":[69],"of":[70,150,171,178],"(well-studied":[71],"in":[72,101,112],"isolation)":[73],"metadata-,":[74],"content-,":[75],"temporal-,":[76],"network-based":[78],"features.":[79],"random":[83],"from":[85,99,168],"our":[86],"seed":[87,124,173],"bank,":[88],"populated":[89],"initially":[90],"by":[91],"previously-labeled":[92],"bots,":[93],"gather":[94],"this":[95],"user's":[96],"followers'":[97],"features":[98,136],"real":[102],"time,":[103],"employ":[105],"ensemble":[108],"anomaly":[109],"method":[111,159],"the":[113,123,127,133,148],"multi-dimensional":[114],"space.":[116],"These":[117],"potential":[118,154],"folded":[121],"into":[122],"bank":[125],"process":[128],"is":[129],"then":[130],"repeated,":[131],"new":[134],"seeds'":[135],"allowing":[137],"adaptively":[140],"BotWalk":[145],"for":[147],"identification":[149],"on":[151],"average":[152],"6,000":[153],"day.":[157],"Our":[158],"allowed":[160],"detect":[163],"7,995":[164],"previously":[165],"undiscovered":[166],"sample":[170],"15":[172],"precision":[177],"90%.":[179]},"counts_by_year":[{"year":2025,"cited_by_count":2},{"year":2024,"cited_by_count":4},{"year":2023,"cited_by_count":5},{"year":2022,"cited_by_count":9},{"year":2021,"cited_by_count":14},{"year":2020,"cited_by_count":14},{"year":2019,"cited_by_count":8},{"year":2018,"cited_by_count":3}],"updated_date":"2026-06-11T09:08:48.828518","created_date":"2017-12-04T00:00:00"}