Introduction

This analysis gives insights into the behavior of nominators within the polkadot network. Nominators are tracked across consecutive sessions using their unique stash address. Within this dataset, each session provides insight into the bonded_amount and a list of targets, representing the nominators’ selected nominations. This approach enables a comparison between sessions, effectively monitoring any changes that occur over time.

The following table illustrates the parameters of the analysis. Note, that there have been some outages in the data collection, but the analysis copes with that and minimizes the impact on the outcome quality.
Parameter Value
Chain polkadot
First Session 5807
Last Session 6351
Missing Tables 100
Total number of unique nominators 54998

Changes over time

In this section, we examine the temporal fluctuations in both the bonded amount and the targets chosen by each nominator. This analysis helps to identify trends and patterns in the behavior of nominators over time.

Bonded Amount: Histogram of changes

The analysis primarily emphasizes the frequency of alterations in the bonded amount. It is essential to note that changes only take effect following a new election, which occurs every 6 sessions. To account for this, it is more meaningful to normalize the frequency on a “per era” basis rather than per session. In this context, if a nominator modifies their bonded amount once throughout 6 sessions, the frequency in the histogram is represented as 1. Conversely, if a nominator adjusts their bonded_amount every session, the frequency is denoted as 6.

There are a few outlier nominators who adjust their bonded amount with remarkable frequency. For the purpose of this analysis, we will concentrate on those with a frequency lying between 0 and 1, ensuring a more representative understanding of typical nominator behavior.

Bonded amount: Changes over sessions

The subsequent graph illustrates the variations in bonded amount across sessions. The frequency displayed is in absolute terms, representing the total number of nominators who altered their bonded_amount within each individual session. This visualization helps to convey the overall trends and patterns in nominators’ behavior over time.