Especially, identifying when public drifts occur is of great importance to different stakeholders, such as government agencies, companies and news agencies, where they can take proactive actions to avoid damages and pay close attentions to new topics/sentiments etc (Hu et al., 2017).
the dynamic nature of drifts/changes makes it a challenging problem, although concept drift analysis can be applied to focus on detecting variation of data distributions over time.