Language Evolution and Computation Bibliography

Language transmission, the passing on of language features such as words between people, is the process of inheritance that underlies linguistic evolution. To understand how language transmission works, we need a mechanistic understanding based on empirical evidence of lasting change of language usage. Here, we analysed 200 million online conversations to investigate transmission between individuals. We find that the frequency of word usage is inherited over conversations, rather than only the binary presence or absence of a word in a person's lexicon. We propose a mechanism for transmission whereby for each word someone encounters there is a chance they will use it more often. Using this mechanism, we measure that, for one word in around every hundred a person encounters, they will use that word more frequently. As more commonly used words are encountered more often, this means that it is the frequencies of words which are copied. Beyond this, our measurements indicate that this per-encounter mechanism is neutral and applies without any further distinction as to whether a word encountered in a conversation is commonly used or not. An important consequence of this is that frequencies of many words can be used in concert to observe and measure language transmission, and our results confirm this. These results indicate that our mechanism for transmission can be used to study language patterns and evolution within populations.

We investigate how the evolution of communication strategies affects signal credibility when there is common interest as well as a conflict between communicating individuals. Taking alarm calls as an example, we show that if the temptation to cheat is low, a single signal is used in the population. If the temptation increases cheaters will erode the credibility of a signal, and an honest mutant using a different signal ('a private code') will be very successful until this, in turn, is cracked by cheaters. In such a system, signal use fluctuates in time and space and hence the meaning of a given signal is not constant. When the temptation to cheat is too large, no honest communication can maintain itself in a Tower of Babel of many signals. We discuss our analysis in the light of the Green Beard mechanism for the evolution of altruism.

Animal communication is typically non-syntactic, which means that signals refer to whole situations. Human language is syntactic, and signals consist of discrete components that have their own meaning. Syntax is a prerequisite for taking advantage of combinatorics, that is, 'making infinite use of finite means'. The vast expressive power of human language would be impossible without syntax, and the transition from non-syntactic to syntactic communication was an essential step in the evolution of human language. We aim to understand the evolutionary dynamics of this transition and to analyse how natural selection can guide it. Here we present a model for the population dynamics of language evolution, define the basic reproductive ratio of words and calculate the maximum size of a lexicon. Syntax allows larger repertoires and the possibility to formulate messages that have not been learned beforehand. Nevertheless, according to our model natural selection can only favour the emergence of syntax if the number of required signals exceeds a threshold value. This result might explain why only humans evolved syntactic communication and hence complex language.