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Description: Elevated emotion network connectivity is thought to leave people vulnerable to become and stay depressed. The mechanism through which this arises is however unclear. Here, we test the idea that the connectivity of emotion networks causes people to suffer more extreme fluctuations in depression over time, rather than necessarily more severe depression. We gathered data from 2 independent samples of N=155 paid students and N=194 citizen scientists who rated their positive and negative emotions on a smartphone app twice a day and completed a weekly depression questionnaire for 8 weeks. We constructed thousands of personalised emotion networks for each participant and tested if connectivity was associated with severity of depression or its variance over 8 weeks. Network connectivity was positively associated with baseline depression severity in citizen scientists, but not paid students. In contrast, 8-week variance of depression was correlated with network connectivity in both samples. When controlling for depression variance, the association between connectivity and baseline depression severity in citizen scientists was no longer significant. We replicated these findings in an independent community sample (N=519). We conclude that elevated network connectivity primarily leads to greater variability in depression symptoms. This variability only translates into increased severity in samples where depression is on average low and positively skewed, causing mean and variance to be more strongly correlated. These findings underscore how emotional network connectivity has bi-directional effects; risk for severe bouts of depression, but also the potential to be harnessed to bring about improvements.