A theoretical model for the associative nature of conference participation

TL;DR

This paper introduces a stochastic model to understand how scientists' previous conference participations influence their future involvement, highlighting the role of early participation in strengthening community ties.

Contribution

The paper presents a novel stochastic model that explains conference participation patterns based on scientists' early engagement and community association.

Findings

Participation probability depends on early participation history.

Active involvement enhances future conference engagement.

Model aligns well with data from six diverse conferences.

Abstract

Participation in conferences is an important part of every scientific career. Conferences provide an opportunity for a fast dissemination of latest results, discussion and exchange of ideas, and broadening of scientists' collaboration network. The decision to participate in a conference depends on several factors like the location, cost, popularity of keynote speakers, and the scientists' association with the community. Here we discuss and formulate the problem of discovering how a scientists' previous participation affects her/his future participations in the same conference series. We develop a stochastic model to examine scientists' participation patterns in conferences and compare our model with data from six conferences across various scientific fields and communities. Our model shows that the probability for a scientist to participate in a given conference series strongly depends on the balance between the number of participations and non-participations during his/her early connections with the community. An active participation in a conference series strengthens the scientists' association with that particular conference community and thus increases the probability of future participations.