Time plays an essential role in the diffusion of information, influence and disease over networks. In many cases we only observe when a node copies information, makes a decision or becomes infected – but the connectivity, transmission rates between nodes and transmission sources are unknown. Inferring the underlying dynamics is of outstanding interest since it enables forecasting, influencing a...

Massive amounts of fake news and conspiratorial content have spread over social media before and after the 2016 US Presidential Elections despite intense fact-checking efforts. How do the spread of misinformation and fact-checking compete? What are the structural and dynamic characteristics of the core of the misinformation diffusion network, and who are its main purveyors? How to reduce the ov...

In real world social networks, there are multiple diffusion processes which are rarely independent. They usually interact with each other in a competitive or cooperative manner. In this paper, motivated by the reinforcement theory in sociology, we model the adoption behavior of users in social networks by a multivariate marked Hawkes process. According to this model, the intensity of a user to ...

Supply chain network enables the enterprises to achieve the purpose of knowledge diffusion complementary. Based on the complex network theory, using the method of combining qualitative analysis and model deduction, we established a knowledge diffusion network model that view staff of supply chain as network node, discussed the mechanism of knowledge diffusion, analysed the main control paramete...

Social media data have been increasingly used to assess the impact of scholarly research. Such data provide complementary metrics (often called altmetrics) to traditional impact indicators. This paper provides a summary on the diffusion of scholarly content in social media, based on a collection of tweets citing papers from a set of 27 academic publishers within various fields between 2011 and ...

Information, disease, and influence diffuse over networks of entities in both natural systems and human society. Analyzing these transmission networks plays an important role in understanding the diffusion processes and predicting future events. However, the underlying transmission networks are often hidden and incomplete, and we observe only the time stamps when cascades of events happen. In t...

This work studies the problem of inferring whether an agent is directly influenced by another agent over an adaptive diffusion network. Agent i influences agent j if they are connected (according to the network topology), and if agent j uses the data from agent i to update its online statistic. The solution of this inference task is challenging for two main reasons. First, only the output of th...

Cascading processes, such as disease contagion, viral marketing, and information diffusion, are a pervasive phenomenon in many types of networks. The problem of devising intervention strategies to facilitate or inhibit such processes has recently received considerable attention. However, a major challenge is that the underlying network is often unknown. In this paper, we revisit the problem of ...

by Lewis Yablonsky, Emeritus Professor of Sociology and Criminology, California State University-Northridge (Published in the American Sociological Association, "Sociological Practice Newsletter" 8/2000 on my acceptance of THE WILLIAM FOOTE WHYTE CAREER AWARD FOR SOCIOLOGICAL PRACTICE at the ASA Meetings 8/2000 in Washington, D.C.; and was the basis for a lecture on 1/25/01 presented at Grand V...

In this paper, I critically examine Stephen Turner‘s (1994) critique of practice theory in light of recent research in neuroscience focused on the discovery the ―mirror neuron system‖ in the pre-frontal motor cortex of humans and other primates. I argue that the strength of two of Turner‘s strongest objections against the sociological version of practice theory—what I refer to as the problem of...