The propagations of diseases, behaviors and information in real systems are rarely
independent of each other, but they are coevolving with strong interactions. To uncover the …

Along with the increase of big data and the advancement of technologies, comprehensive
data-driven knowledge of urban systems is becoming more attainable, yet the connection …

Studies of human mobility in the past decade revealed a number of general scaling laws.
However, to reproduce the scaling behaviors quantitatively at both the individual and …

Bursty dynamics is a common temporal property of various complex systems in nature but it
also characterises the dynamics of human actions and interactions. At the …

To understand quantitatively how scientists choose and shift their research focus over time is
of high importance, because it affects the ways in which scientists are trained, science is …

Social science concerns issues on individuals, relationships, and the whole society. The
complexity of research topics in social science makes it the amalgamation of multiple …

Higher-order structures such as simplicial complexes are ubiquitous in numerous real-world
networks. Empirical evidence reveals that interactions among nodes occur not only through …

Non-Markovian spontaneous recovery processes with a time delay (memory) are ubiquitous
in the real world. How does the non-Markovian characteristic affect failure propagation in …

Wireless big data contain valuable information on users' behaviors and preferences, which
can drive the design and optimization for wireless systems. The fundamental issue is how to …

Similarity is a fundamental measure in network analyses and machine learning algorithms,
with wide applications ranging from personalized recommendation to socio-economic …