Active Sensing of Social Networks

Interactive Sensing in Social Networks

This paper presents models and algorithms for interactive sensing in social networks where individuals act as sensors and the information exchange between individuals is exploited to optimize sensing. Social learning is used to model the interaction between individuals that aim to estimate an underlying state of nature. In this context the following questions are addressed: How can selfinterest...

Estimating the Size and Age-gender Distribution of Women’s Active Social Networks

Background: Network Scale-up (NSU) method is an indirect method for the estimation of hidden behaviors. In NSU, respondents are asked about the number of members they know from a subpopulation of interest (e.g., injecting drug user) and assume that the prevalence of risky behavior in the networks of a random sample of respondents is similar to that of the population. However, first, we need to ...

Perception and Сontent Assessment of Active Users: Russian Language Social Networks

The paper considers studying the perception and assessment of media content in the Russian-language social networks, analyzing the causes that affect the perception and distribution of network content. The importance of language learning and communication in Russian-language social networks, and problems of content effectiveness is determined by the growth in the number and activity of Runet us...

Active Decomposition and Sensing in Networks of Distributed Chemical Sensors

Active sensing enables a sensor to optimize its tunings on-the-fly based on information obtained from previous measurements. When applied to networks of distributed sensors, however, active sensing becomes computationally impractical due to the combinatorial number of sensing configurations. To address this problem, we present an active decomposition and sensing (ADS) method that combines the a...

Information Flow and Active Social Influence in Social Networks