ﻻ يوجد ملخص باللغة العربية
Dail Eireann is the principal chamber of the Irish parliament. The 31st Dail Eireann is the principal chamber of the Irish parliament. The 31st Dail was in session from March 11th, 2011 to February 6th, 2016. Many of the members of the Dail were active on social media and many were Twitter users who followed other members of the Dail. The pattern of following amongst these politicians provides insights into political alignment within the Dail. We propose a new model, called the generalized latent space stochastic blockmodel, which extends and generalizes both the latent space model and the stochastic blockmodel to study social media connections between members of the Dail. The probability of an edge between two nodes in a network depends on their respective class labels as well as latent positions in an unobserved latent space. The proposed model is capable of representing transitivity, clustering, as well as disassortative mixing. A Bayesian method with Markov chain Monte Carlo sampling is proposed for estimation of model parameters. Model selection is performed using the WAIC criterion and models of different number of classes or dimensions of latent space are compared. We use the model to study Twitter following relationships of members of the Dail and interpret structure found in these relationships. We find that the following relationships amongst politicians is mainly driven by past and present political party membership. We also find that the modeling outputs are informative when studying voting within the Dail.
In this article, we study the activity patterns of modern social media users on platforms such as Twitter and Facebook. To characterize the complex patterns we observe in users interactions with social media, we describe a new class of point process
The contagion dynamics can emerge in social networks when repeated activation is allowed. An interesting example of this phenomenon is retweet cascades where users allow to re-share content posted by other people with public accounts. To model this t
A primary goal of social science research is to understand how latent group memberships predict the dynamic process of network evolution. In the modeling of international conflicts, for example, scholars hypothesize that membership in geopolitical co
Mixed membership problem for undirected network has been well studied in network analysis recent years. However, the more general case of mixed membership for directed network remains a challenge. Here, we propose an interpretable model: bipartite mi
Measuring and forecasting migration patterns, and how they change over time, has important implications for understanding broader population trends, for designing policy effectively and for allocating resources. However, data on migration and mobilit