GRHEM first steps (tutorial)

A generalized hyperevent is a time-stamped hyperedge that decomposes into any number of sub-hyperedges, comprising the nodes that occupy a certain event position. An example is given by the publication event of a scientific paper that binds several types of nodes in various positions: the authors of the paper, the cited references, its keywords, the journal in which it is published. Possibly we may also have information on the editor managing the reviewing process. It is plausible that some or all of these positions interact. For example, the references are selected by the authors, but their choice might also be dependent on the paper's keywords, or possibly on the journal or the editor.

Generalized relational hyperevent models (GRHEM) provide a model family for such generalized hyperevents that can test and control for interactions among any number of event positions. This tutorial attempts to give a first intro to GRHEM. Functionality for GRHEMs is available starting from eventnet two that is, version 2.0 or later, currently available as a pre-release eventnet-2.0-pre-2.jar.

Eventnet two provides extended functionality to model such multi-mode hyperevents. Even if the core interest lies in explaining only one or two event positions, for example, the authors and/or references of published papers, the ability to deal with any number of positions allows to specify and test additional effects. For example, it is likely that papers cite other papers that share some of their keywords with higher probability, or there might be a preference to cite papers previously published in the same journal. However, GRHEM do not only allow to specify more effects explaining, e.g., the selection of authors and/or references, but can also be employed to explain any number of event positions simultaneously. For example, it might be unwarranted in general to assume that the keywords or journal of a paper are pre-determined and only then its authors or references are selected (partly dependent on these keywords or journal). A more realistic assumption is that nodes in all, or at least several, event positions are selected mutually dependent on each other. For example, the selection of references of a paper may depend on its authors, keywords, and journal - but the selection of the keywords, or the journal, may also depend on its authors and references. GRHEM allow to simultaneously explain the selection of nodes in any number of event positions, where these choices may be dependent on nodes selected into any combination of other event positions.

This tutorial provides a first introduction to GRHEM. It is recommended to first read, or be otherwise familiar with, three other RHEM tutorials, in particular: the RHEM first steps tutorial, the tutorial for directed RHEM, and the tutorial for the co-evolution of collaboration and reference networks. This tutorial uses a tiny made-up data set on generalized hyperevents representing paper publication and it illustrates the use of eventnet two with the graphical user interface (GUI). As before, it is also possible to execute eventnet with a given configuration file from the command line (as described here), and for larger data sets this is even the recommended way.

Input-data format for generalized hyperevents

To specify