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Furthermore, the details regarding Levels 1 and 2 were narrated.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Findings<\/jats:title>\n<jats:p>By using the proposed technique, <jats:italic>F<\/jats:italic><jats:sub><jats:italic>Score<\/jats:italic><\/jats:sub> obtained for Twitter and Facebook data set was 96.22 and 94.63, respectively.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Research limitations\/implications<\/jats:title>\n<jats:p>Four data sets were used for the experiment and the acquired outcomes demonstrate enhancement over the current existing frameworks.<\/jats:p>\n<\/jats:sec>\n<jats:sec>\n<jats:title content-type=\"abstract-subheading\">Originality\/value<\/jats:title>\n<jats:p>This paper designed a multilevel framework that can be used to detect the anomalies present in the OSN.<\/jats:p>\n<\/jats:sec>","DOI":"10.1108\/lht-01-2019-0023","type":"journal-article","created":{"date-parts":[[2020,1,3]],"date-time":"2020-01-03T07:29:21Z","timestamp":1578036561000},"page":"350-366","source":"Crossref","is-referenced-by-count":19,"title":["Multi-level framework for anomaly detection in social networking"],"prefix":"10.1108","volume":"38","author":[{"given":"Aditya","family":"Khamparia","sequence":"first","affiliation":[]},{"given":"Sagar","family":"Pande","sequence":"additional","affiliation":[]},{"given":"Deepak","family":"Gupta","sequence":"additional","affiliation":[]},{"given":"Ashish","family":"Khanna","sequence":"additional","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-0229-2460","authenticated-orcid":false,"given":"Arun Kumar","family":"Sangaiah","sequence":"additional","affiliation":[]}],"member":"140","reference":[{"key":"key2020061114432305600_ref001","unstructured":"Akoglu, L., McGlohon, M. and Oddball, F.C. 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