ENBIS-18 in Nancy

2 – 25 September 2018; Ecoles des Mines, Nancy (France) Abstract submission: 20 December 2017 – 4 June 2018

An EWMA Control Chart for Categorical Processes with Applications to Social Network Monitoring

5 September 2018, 09:00 – 09:30

Abstract

Submitted by
Marcus Perry
Authors
Marcus Perry (University of Alabama)
Abstract
Statistical process control (SPC) charts have traditionally been applied to manufacturing processes; however, more recent developments highlight their application to social networks. We propose a network monitoring strategy using the exponentially-weighted moving average (EWMA) control chart, with the goal of detecting shifts in the hierarchical tendency of directed graphs over time. Such a strategy might prove useful to an organization's stakeholders when interest lies in monitoring for shifts in the general health of the organization. Although development of the proposed control chart was motivated by a network monitoring problem, our method is generally applicable to multinomial categorical processes. We study the detection performance of our proposed control chart, relative to that of the multinomial cumulative sum (CUSUM) alternative. Results suggest that if the out-of-control shift in the multinomial probabilities cannot be specified a priori, the proposed EWMA control chart should be considered as an alternative to the CUSUM strategy. Application of the proposed method is demonstrated on a real data set; namely, the open source Enron email corpus.
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