Computational Communication


Figure 1 It’s coming!

WHY DID WE DECIDE to propose a new branch on computational communication? What are the main objectives, intended readers, the main features, and the relationships of this approach to various branches of communication? In this Preface, we will try to answer these questions.

Computation Communication (CC) is a new cutting edge branch based on traditional  communication studies, human dynamics,  and network science by collecting, processing and visualizing the data of human digital traces, which is an important part of computational social science or even beyond.

The central concern is to solidly measure the human communication behavior and to challenge classic theories and establish new patterns and laws for insightfully understanding the law of human society.

Figure 1. The Evolving Framework of CC

  • What does computational mean?

Actually, computational is not only the trend in social science, even in natural science, computational is also an emerging trend (e.g., computational biology, computational chemistry). Increasingly, more and more people plunge into the computational world.

1. computational biology

Computational biology involves the development and application of data-analytical and theoretical methods, mathematical modeling and computational simulation techniques to the study of biological, behavioral, and social systems.[1] The field is broadly defined and includes foundations in computer scienceapplied mathematicsstatisticsbiochemistrychemistrybiophysicsmolecular biologygeneticsecologyevolutionanatomyneuroscience, and visualization.[2]   Cited from Wikepedia

Computational biology includes many subfields, e.g., Computational biomodeling, Computational genomics, Computational neuroscience

2. computational chemistry

Computational chemistry is a branch of chemistry that uses principles of computer science to assist in solving chemical problems. It uses the results of theoretical chemistry, incorporated into efficient computer programs, to calculate the structures and properties of molecules and solids. Its necessity arises from the well-known fact that apart from relatively recent results concerning the hydrogen molecular ion (see references therein for more details), the quantum n-body problem cannot be solved analytically, much less in closed form. While its results normally complement the information obtained by chemical experiments, it can in some cases predict hitherto unobserved chemical phenomena. It is widely used in the design of new drugs and materials. Cited from Wikepedia

3. Computational physics

Computational physics is the study and implementation of numerical algorithms to solve problems in physics for which a quantitative theory already exists. It is often regarded as a subdiscipline of theoretical physics but some consider it an intermediate branch between theoretical and experimental physicsPhysicists often have a very precise mathematical theory describing how a system will behave. Unfortunately, it is often the case that solving the theory’s equations ab initio in order to produce a useful prediction is not practical. This is especially true with quantum mechanics, where only a handful of simple models admit closed-form, analytic solutions. In cases where the equations can only be solved approximately, computational methods are often used.Cited from Wikepedia

4. Computational economics

Computational economics is a research discipline at the interface between computer science and economic and management science.[1] Areas and
subjects encompassed include computational modelingof economic systems, whether agent-based,[2] general-equilibrium,[3] macroeconomic,[4] or rational-expectations,[5] computational econometrics and statistics,[6] computational finance, computational tools for the design of automated internet markets, programming tools specifically designed for computational economics, and pedagogical tools for the teaching of computational economics. Some of these areas are unique to computational economics, while others extend traditional areas of economics by solving problems that are difficult to study without the use of computers and associated numerical methods.[7] Cited from Wikepedi

5. Computational linguistics

It’s interesting to see how linguists define computational linguistics:

Computational linguistics might be considered as a synonym of automatic processing of natural language, since the main task of computational linguistics is just the construction of computer programs to process words and texts in natural language. Cited from COMPUTATIONAL LINGUISTICS: Models, Resources, Applications, p25.

6. Computational neuroscience

Computational neuroscience is the study of brain function in terms of the information processing properties of the structures that make up the nervous system.[1] It is an interdisciplinary science that links the diverse fields of neurosciencecognitive scienceand psychology with electrical engineeringcomputer sciencemathematics and physics.

Computational neuroscience is distinct from psychological connectionism and theories of learning from disciplines such as machine learningneural networks and computational learning theory in that it emphasizes descriptions of functional and biologically realistic neurons (and neural systems) and their physiology and dynamics. These models capture the essential features of the biological system at multiple spatial-temporal scales, from membrane currents, protein and chemical coupling to network oscillations, columnar and topographic architecture and learning and memory. These computational models are used to frame hypotheses that can be directly tested by current or future biological and/or psychological experiments.

Here is a video introducing computational social science.

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