A New Model for Information Diffusion in Heterogeneous Social Networks

This paper discusses a new model for the diffusion of information through heterogeneous social networks. In earlier models, when information was given by one actor to another the transmitter did not retain the information. The new model is an improvement on earlier ones because it allows a transmitter of information to retain that information after telling it to somebody else. Consequently, the new model allows more actors to have information during the information diffusion process. The model provides predictions of diffusion times in a given network at the global, dyadic, and individual levels. This leads to straightforward generalizations of network measures, such as closeness centrality and betweenness centrality, for research problems that focus on the efficiency of information transfer in a network. We analyze in detail how information diffusion times and centrality measures depend on a series of network measures, such as degrees and bridges. One important finding is that predictions about the time actors need to spread information in the network differ considerably between the new and old models, while the predictions about the time needed to receive information hardly differ. Finally, some cautionary remarks are made about using the model in empirical research.     

Accelerated Failure–Time Mover–Stayer Regression Models for the Analysis of Last–Episode Data

This article introduces new models for the analysis of last–episode data—that is, data about the timing of the last occurrence of a repeatable event. The new models are elaborations and extensions of a particular model for backward recurrence times from a renewal process introduced by Allison (1985) , and they are accelerated failure–time mover–stayer regression models that permit the separation of covariate effects on event timing from those on event occurrence. Using the data of last residential move from the 1990 Census of Population and Housing, an application of the models, which are found to fit the data adequately, shows distinct patterns in the effects of home ownership, gender, race/ethnicity, education, marital experience, and age group on residential mobility. The patterns differ regarding the relative importance and direction of influence between the effects on the duration of residence in the same house or apartment and the effects on the lifetime probability of not experiencing any residential move.     

The Impact of Ovarian Cancer on Life Expectancy in Japan

The purpose of this study was to determine how life expectancy is modified by ovarian cancer from 1950-2000. The contributions of ovarian cancer to life expectancy were estimated. The age characteristics of ovarian cancer were detected using the Gompertz relational mortality model. The patterns between years of potential life lost (YPLL) and mortality were obtained by fitting a linear regression equation to the natural logarithm of their ratios. YPLLs are substantially higher in Ireland than in Japan. However, the rates of change were much higher in Japan than in Ireland. YPLLs changed from 0.02 year in 1950 to 0.12 year in 2000. In Japan, there was a sixfold increase in the proportion of YPLLs for death from ovarian cancer relative to those for death from gynaecological cancers during the last half century. The impact of ovarian cancer on life expectancy clearly increased and the age-specific mortality tend to ageing.