As you can see some features are very stable through the time series (post-2011) like Extraversion. Is there an algorithm to remove features that do not have much variation compared to the other features?
Step 1. Identify a measure of variation for a feature.
Step 2. Remove all features for which this measure is below some threshold (or is below that of msot other features).
There are many measures of variability that you could use in step 1: standard deviation, interquartile range, range (max minus min), median absolute deviation, and more. Any of these are probably reasonable.