Why do clickbait headlines attract so many readers? Columnist Jacob Aron links this tendency to an unexpected origin: a mathematical system that influenced much of contemporary technology. Information theory accounts for the appeal of certain phrases. Clickbait succeeds by hinting at details while withholding them, often by crafting headlines that convey little substance. A direct headline like “Trump wins election” delivers more content than a vague one like “You’ll never believe who just won the election,” even though the second uses more words. This seems contradictory, yet a mathematical approach clarifies it. Developed in 1948 at the start of the computing era, information theory shaped much of today’s digital infrastructure. Mathematician Claude Shannon at Bell Labs sought to address reliable transmission despite poor signals. The lab, then part of AT&T, functioned like a leading research center and produced key inventions including the transistor. Shannon’s contribution proved equally significant. He determined that the meaning of a message does not affect its transmission. As stated in his paper, semantic elements are separate from the engineering task. What counts is the unexpected nature of the message, expressed as the likelihood of selecting that particular message. Messages can be assigned probabilities because they use a finite set of symbols. Consider transmitting coin flip results with H or T. A fair coin yields equal 50 percent chances, so each result provides new information. A biased coin that always shows heads transmits no new data. Shannon created a formula called entropy to measure this quantity: H equals negative sum of p(x) times log of p(x). Here x stands for the message, and p(x) its probability. The logarithm converts the value, and the sum covers all possible messages. The choice of base sets the information unit; base 2 produces bits. These bits form the foundation of digital systems. For a fair coin the calculation yields one bit; for the biased coin it yields zero. Journalism values novelty in a similar way, as routine events rarely qualify as news while unusual ones do. Shannon focused only on probability, not meaning, which marks a key difference from reporting practices.
