Review of statistical network analysis: models, algorithms, and software

M Salter-Townshend, A White, I Gollini, TB Murphy - 2012 - researchrepository.ucd.ie
The analysis of network data is an area that is rapidly growing, both within and outside of the
discipline of statistics. This review provides a concise summary of methods and models used …

Joint modeling of multiple network views

I Gollini, TB Murphy - Journal of Computational and Graphical …, 2016 - Taylor & Francis
Latent space models (LSM) for network data rely on the basic assumption that each node of
the network has an unknown position in a D-dimensional Euclidean latent space: generally …

A two-stage working model strategy for network analysis under hierarchical exponential random graph models

M Cao, Y Chen, K Fujimoto… - 2018 IEEE/ACM …, 2018 - ieeexplore.ieee.org
Social network data are complex and dependent data. At the macro-level, social networks
often exhibit clustering in the sense that social networks consist of communities; and at the …

Model-based clustering for network data

TB Murphy - Handbook of Cluster Analysis. Chapman & Hall …, 2016 - api.taylorfrancis.com
This chapter reviews some of the most popular statistical model-based methods for
clustering network datasets. In particular, the stochastic block model, the mixed membership …

Analysing my Facebook friends

M Salter-Townshend - Significance, 2012 - academic.oup.com
Analysing My Facebook Friends | Significance | Oxford Academic Skip to Main Content
Advertisement Oxford Academic Journals Books Search Menu Information Account Menu …

3 Quadratic Error and k-Means

SAS Using 2nd, CRC Press - Published Titles - api.taylorfrancis.com
3 Quadratic Error and k-Means Page 47 3 Quadratic Error and k-Means R efer ences RC
Amorim, B. Mirkin 2012Minkowskimetric, featureweighting and anomalous cluster initializing in …

[PDF][PDF] BIG DATA AND'SOCIAL'REPUTATION: A FINANCIAL EXAMPLE

P Cerchiello - BOOK OF ABSTRACTS - researchgate.net
The role of online opinions and of social forum is continuously gaining great interest and
influence. Thus it is important to track such information and to employ efficient statistical …

MATH 100 Topic Analyzing Your Social Network Data

L Kang - math.iit.edu
With the growth of websites such as Facebook, Google Plus and LinkedIn, social networking
is enjoying an increasingly large public profile. There is also an increasing amount of time …