Jiachen Sun

Sun Yat-Sen University | SYSU · Department of Computer Science

The evolution processes of complex systems carry key information in the systems’ functional properties. Applying machine learning algorithms, we demonstrate that the historical formation process of various networked complex systems can be extracted, including protein-protein interaction, ecology, and social network systems. The recovered evolution...

The COVID-19 infection cases have surged globally, causing devastations to both the society and economy. A key factor contributing to the sustained spreading is the presence of a large number of asymptomatic or hidden spreaders, who mix among the susceptible population without being detected or quarantined. Due to the continuous emergence of new vi...

Bipartite network is crucial for recommendation systems as user-product behaviors are thoroughly described by bipartite interactions. Almost all of the state-of-the-art network compression algorithms are designed for general networks without harnessing the unique bipartite structure. Until 2017, Basu and Varshney proposed a compression algorithm, B...

It is widely believed that information spread on social media is a percolation process, with parallels to phase transitions in theoretical physics. However, evidence for this hypothesis is limited, as phase transitions have not been directly observed in any social media. Here, through an analysis of 100 million Weibo and 40 million Twitter users, w...

As a powerful and low-cost instant information dissemination platform, large-scale online social networks (OSNs) play a pivotal role in shaping our modern information age. The efficient detection of wide-spreading information in OSNs is very important in many aspects including public opinion supervision, social governance, stock markets, counter-te...

The COVID-19 infection cases have surged globally, causing devastations to both the society and economy. A key factor contributing to the sustained spreading is the presence of a large number of asymptomatic or hidden spreaders, who mix among the susceptible population without being detected or quarantined. Here we propose an effective non-pharmaco...

It is widely believed that information spread on social media is a percolation process, with parallels to phase transitions in theoretical physics. However, evidence for this hypothesis is limited, as phase transitions have not been directly observed in any social media. Here, through analysis of 100 million Weibo and 40 million Twitter users, we i...

As the novel coronavirus disease 2019 (COVID-19) has become a Public Health Emergency of International Concern, it is greatly significant to accurately predict the disease's incoming trend. Herein, we performed a stage-rolling Susceptible-Exposed-Infectious-Recovered (SEIR) model to measure the evolution of the basic reproduction number of COVID-19...

The code and processed data for 'Comparative COVID-19 Analysis of Google Trend and Twitter Among 50 U.S. States'

Structure prediction is an important and widely studied problem in network science and machine learning, finding its applications in various fields. Despite the significant progress in prediction algorithms, the fundamental predictability of structures remains unclear, as networks’ complex underlying formation dynamics are usually unobserved or dif...

bond and site percolation MATLAB codes

Source Code and Data for Paper: Revealing the Predictability of Intrinsic Structure in Complex Networks

In this Letter, the authors propose a novel low-density parity-check (LDPC) coding scheme to transmit extra bits aided by rotated signal constellations without any additional cost in transmission power or bandwidth. In the proposed scheme, the LDPC coded data are modulated by a rotated two-dimensional signal constellation, in which the rotation ang...

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Networks in nature not only depend on each other but also have internal community structures, such as infrastructure networks with links within and across geographic regions. The communities play an important role when the networks undergo localized failures in specific regions, for instance when natural disasters or economic sanctions disrupt a lo...

The network dismantling problem is one of the most fundamental problems in network science. It aims to identify the minimum number of nodes, such that after their removal the network is broken into many disconnected pieces with a sub-extensive size. However, the identification of the minimum removed nodes belongs to the class of nondeterministic po...

Modern online social network platforms are replacing traditional media due to their effectiveness in both spreading information and communicating opinions. One of the key problems in these online platforms is to predict the global spread range of any given information. Due to its gigantic size as well as time-varying dynamics, an online social netw...

In this paper, we propose a new coding scheme for space image transmission, which combines the unequal error protection (UEP) by partial superposition transmission (referred to as UEP-by-PST) with coded modulation standards recommended by the Consultative Committee for Space Data Systems (CCSDS). The raw image is first processed by the recommended...