Expression of Concern: Multi-level framework for anomaly detection in social networking

The publisher is issuing an Expression of Concern for the following article, Khamparia A, Pande S, Gupta D, Khanna A, Sangaiah AK (2020), “Multi-level framework for anomaly detection in social networking”. Library Hi Tech, Vol. 38 No. 2 pp. 350-366, doi: Link to the DOI. An investigation by the publisher identified the use of multiple tortured and unusual phrases, including “K-closest neighbors” (K-nearest neighbours), “abnormality recognition”, “irregularity recognition”, and “oddity location” (anomaly detection), “distinguishing proof” and “recognizable proof” (identification), “named information” (labelled data) and “preparation dataset” (training dataset). The authors cooperated with this investigation but failed to provide a satisfactory explanation to these concerns. Emerald's publishing ethics policies make it clear that authors must be accountable for the accuracy and integrity of the work submitted. While the article's findings, theoretical contributions and conclusions currently remain intact, the journal and publisher have, however, taken the decision to publish an Expression of Concern to alert readers to this issue and as trust in the content is central to the integrity of the publication process. This decision has been informed by COPE's guidelines on Expressions of Concern and Emerald's publishing ethics policies. The publisher of the journal sincerely apologizes to the readers of this work.