Modeling multiple hashtag time series

Nov 8 - Nov 15

Principal Components

Supposing we now have \(N\) hashtag point processes. Here we present analysis based on the daily count process.

We denote the daily counts for hashtag \(i\) as \(x_i(t)\), where \(t\) takes integer values in \([t_{\min}, t_{\max}]\). In our data, we have the year-long time window of 2012.

In the following, we show the daily counts with aligned time axis for a few top-trending hashtags.

The daily count series for 10 top-trending hashtags: “bullying” “bully” “stopbullying” “bullymovie” “spiritday” “ripamandatodd” “lgbt” “bullied” “teamfollowback” “ripboybeliebermartin”