Social Effects in Science: Modelling Agents for a Better Scientific Practice

TL;DR

This paper presents an agent-based model to analyze how social influences and experimental evidence affect scientific consensus, highlighting the importance of retiring old scientists and the interplay between social and empirical factors.

Contribution

It introduces an Opinion Dynamics agent model incorporating external experimental influence to study social effects in scientific practice.

Findings

Retirement of old scientists impacts acceptance of new theories

Social influence can sometimes overshadow experimental evidence

The model identifies conditions where social effects are negligible or significant

Abstract

Science is a fundamental human activity and we trust its results because it has several error-correcting mechanisms. Its is subject to experimental tests that are replicated by independent parts. Given the huge amount of information available, scientists have to rely on the reports of others. This makes it possible for social effects to influence the scientific community. Here, an Opinion Dynamics agent model is proposed to describe this situation. The influence of Nature through experiments is described as an external field that acts on the experimental agents. We will see that the retirement of old scientists can be fundamental in the acceptance of a new theory. We will also investigate the interplay between social influence and observations. This will allow us to gain insight in the problem of when social effects can have negligible effects in the conclusions of a scientific community and when we should worry about them.