Research on the Influence of Information Iterative Propagation on Complex Network Structure
Yinuo Qian1, Fuzhong Nian1, Zheming Wang1
1School of Computer and Communication, Lanzhou University of Technology, Lanzhou, China.
Big Data
|July 27, 2024
Summary
This study visualizes how information propagation dynamics alter network structures. It introduces node participation to quantify user influence on information spread and analyzes micro (chain edges) and macro (community division) structural changes.
Area of Science:
- Network Science
- Information Dynamics
- Complex Systems
Background:
- Network structures evolve due to dynamic propagation processes.
- Iterative information propagation influences connection strengths and network evolution over time.
- Existing research often focuses on temporal network construction, overlooking propagation dynamics' impact on structure.
Purpose of the Study:
- To visualize and quantify how propagation dynamics influence complex network structure changes.
- To analyze both micro-level (chain edges) and macro-level (community division) structural alterations.
- To propose a metric for quantifying user influence on information propagation.
Main Methods:
- Constructing weighted networks based on iterative information propagation analysis.
- Simulating information propagation in diverse network types.
- Proposing and applying 'node participation' to quantify user influence.
Main Results:
- Demonstrated that iterative propagation leads to micro-level changes like chain edge formation.
- Showcased macro-level structural changes through community division analysis.
- Successfully quantified the influence of different users on information propagation using node participation.
Conclusions:
- Information propagation dynamics are key drivers of complex network structural evolution.
- Node participation effectively quantifies individual user impact on network-wide information spread.
- Analyzing chain edges and community structures provides a comprehensive understanding of propagation's influence.
Related Concept Videos
01:23Propagation of Action Potentials
5.5K
The propagation of an action potential refers to the process by which a nerve impulse, or "action potential," travels along a neuron.
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...
Neurons (nerve cells) have a resting membrane potential, with a slightly negative charge inside compared to outside. This is maintained by ion channels, such as sodium (Na+) and potassium (K+) channels, which control the flow of ions. When a stimulus, like a touch or a signal from another neuron, triggers the neuron, sodium channels open, allowing sodium ions to...
5.5K
01:10Propagation of Uncertainty from Systematic Error
496
The atomic mass of an element varies due to the relative ratio of its isotopes. A sample's relative proportion of oxygen isotopes influences its average atomic mass. For instance, if we were to measure the atomic mass of oxygen from a sample, the mass would be a weighted average of the isotopic masses of oxygen in that sample. Since a single sample is not likely to perfectly reflect the true atomic mass of oxygen for all the molecules of oxygen on Earth, the mass we obtain from this...
496
00:59Propagation of Uncertainty from Random Error
661
An experiment often consists of more than a single step. In this case, measurements at each step give rise to uncertainty. Because the measurements occur in successive steps, the uncertainty in one step necessarily contributes to that in the subsequent step. As we perform statistical analysis on these types of experiments, we must learn to account for the propagation of uncertainty from one step to the next. The propagation of uncertainty depends on the type of arithmetic operation performed on...
661
01:07Propagation of Waves
2.3K
When a wave propagates from one medium to another, part of it may get reflected in the first medium, and part of it may get transmitted to the second medium. In such a case, the interface of the two mediums can be considered as a boundary that is neither fixed nor free.
Consider a scenario where a wave propagates from a string of low linear mass density to a string of high linear mass density. In such a case, the reflected wave is out of phase with respect to the incident wave, however the...
Consider a scenario where a wave propagates from a string of low linear mass density to a string of high linear mass density. In such a case, the reflected wave is out of phase with respect to the incident wave, however the...
2.3K
01:25Network Function of a Circuit
276
Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.
276
01:24Sequence Networks of Rotating Machines
98
A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...
98