Capturing Dynamics of Information Diffusion in SNS: A Survey of Methodology and Techniques

Studying information diffusion in SNS (Social Networks Service) has remarkable significance in both academia and industry. Theoretically, it boosts the development of other subjects such as statistics, sociology, and data mining. Practically, diffusion modeling provides fundamental support for many downstream applications (e.g., public opinion monitoring, rumor source identification, and viral marketing). Tremendous efforts have been devoted to this area to understand and quantify information diffusion dynamics. This survey investigates and summarizes the emerging distinguished works in diffusion modeling. We first put forward a unified information diffusion concept in terms of three components: information, user decision, and social vectors, followed by a detailed introduction of the methodologies for diffusion modeling. And then, a new taxonomy adopting hybrid philosophy (i.e., granularity and techniques) is proposed, and we made a series of comparative studies on elementary diffusion models under our taxonomy from the aspects of assumptions, methods, and pros and cons. We further summarized representative diffusion modeling in special scenarios and significant downstream tasks based on these elementary models. Finally, open issues in this field following the methodology of diffusion modeling are discussed.

Highly selective behaviour of colon adenoma after administration of EMR composition and its HCT116-based model.

When applying the improved composition of the solution used during endoscopic mucosal resection (EMR), we observed unexpectedly large and quantitatively significant differences in adenoma response vs. healthy tissue of the surrounding GIT tract, namely, the selective reaction enhancing the adenoma volume and differentiated colour. The in vitro experiments on the model neoplasia cell line HCT116 suggest that the robust differences in the response of starving cells can be traced down principally to tetrastarch digestion and the enhanced metabolic rate of neoplastic cells. The neoplastic tissue grows into several intestine layers so that submucosal injection of iso-oncotic tetrastarch compound leads to degradation of starch and production of oncotic molecules in submucosa transported by facilitated transport into the neoplastic tissue. The colour distinction is due to concentration differences of the reporting dye between three separated compartments, further enhancing the utility of the contrasting mixture. The diffusion dynamics shall be tuneable by optimizing starch composition, improving desirable pharmacokinetics.

Highly selective behaviour of colon adenoma after administration of EMR composition and its HCT116-based model.

When applying the improved composition of the solution used during endoscopic mucosal resection (EMR), we observed unexpectedly large and quantitatively significant differences in adenoma response vs. healthy tissue of the surrounding GIT tract, namely, the selective reaction enhancing the adenoma volume and differentiated colour. The in vitro experiments on the model neoplasia cell line HCT116 suggest that the robust differences in the response of starving cells can be traced down principally to tetrastarch digestion and the enhanced metabolic rate of neoplastic cells. The neoplastic tissue grows into several intestine layers so that submucosal injection of iso-oncotic tetrastarch compound leads to degradation of starch and production of oncotic molecules in submucosa transported by facilitated transport into the neoplastic tissue. The colour distinction is due to concentration differences of the reporting dye between three separated compartments, further enhancing the utility of the contrasting mixture. The diffusion dynamics shall be tuneable by optimizing starch composition, improving desirable pharmacokinetics.

Cultural diffusion dynamics depend on behavioural production rules

Culture is an outcome of the acquisition of knowledge about behaviour through social transmission, and its subsequent production. Transmission and production are often discussed interchangeably or modeled separately, yet to date, no study has accounted for both processes and explored their interaction. We present a generative model that integrates the two in order to explore how variation in either might shape cultural diffusion dynamics. Agents make behavioural choices that change as they learn from their behavioural productions. Their repertoires also change over time, and the social transmission of behaviours depends on their frequency. We diffuse a novel behaviour through social networks across a large parameter space to demonstrate how accounting for both transmission and production reveals dependencies between individual-level behavioural production rules and population-level diffusion dynamics. We then investigate how such dependencies might affect the performance of two commonly used inferential models for social learning; Network-based Diffusion Analysis (NBDA), and Experienced Weighted Attraction models (EWA). By clarifying the distinction between acquisition and usage, we illuminate often-overlooked theoretical differences between social learning and social influence. These distinctions yield consequences and new considerations for how inferential methods are applied to empirical studies of culture.

Precise measurements of chromatin diffusion dynamics by modeling using Gaussian processes

The spatiotemporal organization of chromatin influences many nuclear processes: from chromosome segregation to transcriptional regulation. To get a deeper understanding of these processes, it is essential to go beyond static viewpoints of chromosome structures, to accurately characterize chromatin’s diffusion properties. We present GP-FBM: a computational framework based on Gaussian processes and fractional Brownian motion to extract diffusion properties from stochastic trajectories of labeled chromatin loci. GP-FBM uses higher-order temporal correlations present in the data, therefore, outperforming existing methods. Furthermore, GP-FBM allows to interpolate incomplete trajectories and account for substrate movement when two or more particles are present. Using our method, we show that average chromatin diffusion properties are surprisingly similar in interphase and mitosis in mouse embryonic stem cells. We observe surprising heterogeneity in local chromatin dynamics, correlating with potential regulatory activity. We also present GP-Tool, a user-friendly graphical interface to facilitate usage of GP-FBM by the research community.