{"id":"https://openalex.org/W2751287462","doi":"https://doi.org/10.1109/iscc.2017.8024692","title":"Spam comments detection with self-extensible dictionary and text-based features","display_name":"Spam comments detection with self-extensible dictionary and text-based features","publication_year":2017,"publication_date":"2017-07-01","ids":{"openalex":"https://openalex.org/W2751287462","doi":"https://doi.org/10.1109/iscc.2017.8024692","mag":"2751287462"},"language":"en","primary_location":{"id":"doi:10.1109/iscc.2017.8024692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscc.2017.8024692","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Symposium on Computers and Communications (ISCC)","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/A5101708694","display_name":"Qiang Zhang","orcid":"https://orcid.org/0000-0002-2436-3514"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":true,"raw_author_name":"Qiang Zhang","raw_affiliation_strings":["Institute of Big Data Technologies, Peking University, Shenzhen, P.R.China"],"affiliations":[{"raw_affiliation_string":"Institute of Big Data Technologies, Peking University, Shenzhen, P.R.China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5103006104","display_name":"Chenwei Liu","orcid":"https://orcid.org/0000-0001-9291-3103"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Chenwei Liu","raw_affiliation_strings":["Institute of Big Data Technologies, Peking University, Shenzhen, P.R.China"],"affiliations":[{"raw_affiliation_string":"Institute of Big Data Technologies, Peking University, Shenzhen, P.R.China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5101057662","display_name":"Shangru Zhong","orcid":null},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Shangru Zhong","raw_affiliation_strings":["Institute of Big Data Technologies, Peking University, Shenzhen, P.R.China"],"affiliations":[{"raw_affiliation_string":"Institute of Big Data Technologies, Peking University, Shenzhen, P.R.China","institution_ids":["https://openalex.org/I20231570"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5078920845","display_name":"Kai Lei","orcid":"https://orcid.org/0000-0001-9197-895X"},"institutions":[{"id":"https://openalex.org/I20231570","display_name":"Peking University","ror":"https://ror.org/02v51f717","country_code":"CN","type":"education","lineage":["https://openalex.org/I20231570"]}],"countries":["CN"],"is_corresponding":false,"raw_author_name":"Kai Lei","raw_affiliation_strings":["Institute of Big Data Technologies, Peking University, Shenzhen, P.R.China"],"affiliations":[{"raw_affiliation_string":"Institute of Big Data Technologies, Peking University, Shenzhen, P.R.China","institution_ids":["https://openalex.org/I20231570"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":4,"corresponding_author_ids":["https://openalex.org/A5101708694"],"corresponding_institution_ids":["https://openalex.org/I20231570"],"apc_list":null,"apc_paid":null,"fwci":1.4509,"has_fulltext":false,"cited_by_count":4,"citation_normalized_percentile":{"value":0.86981448,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":97},"biblio":{"volume":"23","issue":null,"first_page":"1225","last_page":"1230"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T11644","display_name":"Spam and Phishing Detection","score":1.0,"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":1.0,"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":0.9991000294685364,"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/T11550","display_name":"Text and Document Classification Technologies","score":0.9984999895095825,"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":0.8763428330421448},{"id":"https://openalex.org/keywords/microblogging","display_name":"Microblogging","score":0.6820861101150513},{"id":"https://openalex.org/keywords/social-media","display_name":"Social media","score":0.6591071486473083},{"id":"https://openalex.org/keywords/information-retrieval","display_name":"Information retrieval","score":0.5890237092971802},{"id":"https://openalex.org/keywords/construct","display_name":"Construct (python library)","score":0.5615177154541016},{"id":"https://openalex.org/keywords/publication","display_name":"Publication","score":0.5241397023200989},{"id":"https://openalex.org/keywords/field","display_name":"Field (mathematics)","score":0.5016231536865234},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.4653530716896057},{"id":"https://openalex.org/keywords/semantic-analysis","display_name":"Semantic analysis (machine learning)","score":0.4295836091041565},{"id":"https://openalex.org/keywords/natural-language-processing","display_name":"Natural language processing","score":0.4213711619377136},{"id":"https://openalex.org/keywords/world-wide-web","display_name":"World Wide Web","score":0.35876739025115967}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.8763428330421448},{"id":"https://openalex.org/C143275388","wikidata":"https://www.wikidata.org/wiki/Q92438","display_name":"Microblogging","level":3,"score":0.6820861101150513},{"id":"https://openalex.org/C518677369","wikidata":"https://www.wikidata.org/wiki/Q202833","display_name":"Social media","level":2,"score":0.6591071486473083},{"id":"https://openalex.org/C23123220","wikidata":"https://www.wikidata.org/wiki/Q816826","display_name":"Information retrieval","level":1,"score":0.5890237092971802},{"id":"https://openalex.org/C2780801425","wikidata":"https://www.wikidata.org/wiki/Q5164392","display_name":"Construct (python library)","level":2,"score":0.5615177154541016},{"id":"https://openalex.org/C41458344","wikidata":"https://www.wikidata.org/wiki/Q732577","display_name":"Publication","level":2,"score":0.5241397023200989},{"id":"https://openalex.org/C9652623","wikidata":"https://www.wikidata.org/wiki/Q190109","display_name":"Field (mathematics)","level":2,"score":0.5016231536865234},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.4653530716896057},{"id":"https://openalex.org/C2777946921","wikidata":"https://www.wikidata.org/wiki/Q7449044","display_name":"Semantic analysis (machine learning)","level":2,"score":0.4295836091041565},{"id":"https://openalex.org/C204321447","wikidata":"https://www.wikidata.org/wiki/Q30642","display_name":"Natural language processing","level":1,"score":0.4213711619377136},{"id":"https://openalex.org/C136764020","wikidata":"https://www.wikidata.org/wiki/Q466","display_name":"World Wide Web","level":1,"score":0.35876739025115967},{"id":"https://openalex.org/C199360897","wikidata":"https://www.wikidata.org/wiki/Q9143","display_name":"Programming language","level":1,"score":0.0},{"id":"https://openalex.org/C202444582","wikidata":"https://www.wikidata.org/wiki/Q837863","display_name":"Pure mathematics","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/C112698675","wikidata":"https://www.wikidata.org/wiki/Q37038","display_name":"Advertising","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}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/iscc.2017.8024692","is_oa":false,"landing_page_url":"https://doi.org/10.1109/iscc.2017.8024692","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"2017 IEEE Symposium on Computers and Communications (ISCC)","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/4","display_name":"Quality Education","score":0.8799999952316284}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":21,"referenced_works":["https://openalex.org/W1233141674","https://openalex.org/W1560851690","https://openalex.org/W1851422430","https://openalex.org/W1964362931","https://openalex.org/W1987732684","https://openalex.org/W1993081839","https://openalex.org/W2051183465","https://openalex.org/W2059009656","https://openalex.org/W2101536553","https://openalex.org/W2152775624","https://openalex.org/W2153579005","https://openalex.org/W2296421757","https://openalex.org/W2333269343","https://openalex.org/W2346278349","https://openalex.org/W2396651124","https://openalex.org/W2501941158","https://openalex.org/W2963871344","https://openalex.org/W4294170691","https://openalex.org/W6648344142","https://openalex.org/W6682691769","https://openalex.org/W6697481423"],"related_works":["https://openalex.org/W2728430307","https://openalex.org/W2107786128","https://openalex.org/W2053241453","https://openalex.org/W2153980712","https://openalex.org/W2537388533","https://openalex.org/W2978974359","https://openalex.org/W2036556872","https://openalex.org/W2021183651","https://openalex.org/W2017590198","https://openalex.org/W2353191283"],"abstract_inverted_index":{"The":[0,56],"new":[1,52],"social":[2,35],"media":[3],"have":[4],"become":[5],"popular":[6],"for":[7,99],"information":[8],"spreading,":[9],"allowing":[10],"online":[11],"users":[12],"to":[13,41,96,115],"publish":[14],"latest":[15],"events":[16],"and":[17,48,93],"personal":[18],"opinions.":[19],"However,":[20],"massive":[21],"spam":[22,31,87,91,101,117,130],"comments":[23,32,118,131],"seriously":[24],"decrease":[25],"users'":[26],"reading":[27],"experience.":[28],"To":[29],"detect":[30,129],"in":[33,65,132],"Chinese":[34,86,133],"media,":[36],"we":[37,76,104],"employ":[38],"semantic":[39,61],"analysis":[40,58,72],"build":[42],"the":[43,70],"self-extensible":[44],"dictionary":[45,92],"which":[46,63,81,112],"updates":[47],"extends":[49],"itself":[50],"with":[51],"cyber":[53],"words":[54],"automatically.":[55],"Semantic":[57],"brings":[59],"extra":[60],"features":[62,95],"helps":[64],"text":[66],"classification.":[67],"Based":[68],"on":[69],"statistical":[71],"of":[73,85,110],"microblogging":[74,134],"comments,":[75],"select":[77],"four":[78],"text-based":[79,94],"features,":[80],"basically":[82],"represent":[83],"characteristics":[84],"comments.":[88,102],"We":[89],"use":[90],"construct":[97],"classifiers":[98],"detecting":[100],"Finally,":[103],"achieve":[105],"an":[106],"average":[107],"detection":[108,119],"accuracy":[109],"93.6%,":[111],"is":[113],"preferable":[114],"existing":[116],"methods.":[120],"Experimental":[121],"results":[122],"demonstrate":[123],"that":[124],"our":[125],"method":[126],"can":[127],"effectively":[128],"field.":[135]},"counts_by_year":[{"year":2022,"cited_by_count":1},{"year":2018,"cited_by_count":3}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}