Amount of self-information and "dense information"

Amount of self-information and "dense information"

Information theory states that the lower the probability of an event, the greater the amount of self-information. For example, when an event with a probability of 0.01 occurs, the weight of information it brings is much greater than that of an event with a probability of 0.5. This "scarcity and surprise" can be quantified by the concept of "amount of self-information" as formulated by Shannon.

We can also see this principle in modern social networking and news dissemination. Rare and high-impact" information, such as fake news or information about cheap sales, attracts people's attention and spreads easily, regardless of its authenticity. This can be explained both mathematically and psychologically.

In fact, an MIT study found that false information on Twitter spreads about six times faster than the truth. This is due to the "large amount of self-information" that scarce information has, which humans subconsciously judge as valuable. Add to that network structure and bias (the desire to share surprises), and "dense information" has a significant social impact.

Thus, the formula "low probability = dense information" provides a clue to understanding contemporary information diffusion mechanisms.