Tweeting #RamNavami: A Comparison of Approaches to Analyzing Bipartite Networks

Bipartite networks, also known as two-mode networks or affiliation are a class of in which actors objects partitioned into two sets, with interactions taking place across but not within sets. These omnipresent society, encompassing phenomena such student-teacher interactions, coalition structures and international treaty participation. With growing data availability proliferation statistical estimators software, scholars have increasingly sought to understand the methods available model data-generating processes these networks. This article compares three for doing so: (a) Logit (b) bipartite Exponential Random Graph Model (ERGM) (c) Relational Event (REM). comparison demonstrates relevance choices respect dependence structures, temporality, parameter specification structure. Considering example Ram Navami, Hindu festival celebrating birth Lord Ram, ego network tweets using #RamNavami on 21April 2021 is examined. The results analysis illustrate that critical modelling make difference estimated parameters conclusions be drawn from them.