Abstract
Predicting a transition point in behavioral data should take into account the complexity of the signal being influenced by contextual factors. In this paper, we propose to analyze changes in the embedding dimension as contextual information indicating a proceeding transitive point, called OPtimal Embedding tRANsition Detection (OPERAND). Three texts were processed and translated to time-series of emotional polarity. It was found that changes in the embedding dimension proceeded transition points in the data. These preliminary results encourage further research into changes in the embedding dimension as generic markers of an approaching transition point.
Highlights
When observing a time-series, it is important to predict significant changes such as the burst of an epidemic [1], the collapse of a political regime [2], or the change in a person’s mood
In a recent comment published in Nature, Boettiger and Hastings argue that ‘‘Truly generic signals warning of tipping points are unlikely to exist’’ and that researchers should study ‘‘transitions specific to real systems’’ [8]
A change in the dimensionality of a system may be indicated by a change of the embedding dimension necessary for unfolding the dynamics represented by a time-series
Summary
When observing a time-series, it is important to predict significant changes such as the burst of an epidemic [1], the collapse of a political regime [2], or the change in a person’s mood. In recent years there have been intensive efforts in identifying early-warning signals of an approaching tipping-point [3,4,5]. While several generic signals have been identified, it was recently argued [6] that there is ‘‘no single best indicator or method for identifying an upcoming transition’’ and that ‘‘all methods required specific data-treatment to yield sensible signals’’. There is no single and simple generic indicator of an approaching-tipping point. This conclusion probably holds for non-catastrophic transitions [7] that are much more frequent than catastrophic transitions. In a recent comment published in Nature, Boettiger and Hastings argue that ‘‘Truly generic signals warning of tipping points are unlikely to exist’’ and that researchers should study ‘‘transitions specific to real systems’’ [8]
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