  We analyze online collective evaluation processes through positive and
negative votes in various social media. We find two modes of collective
evaluations that stem from the existence of filter bubbles. Above a threshold
of collective attention, negativity grows faster with positivity, as a sign of
the burst of a filter bubble when information reaches beyond the local social
context of a user. We analyze how collectively evaluated content can reach
large social contexts and create polarization, showing that emotions expressed
through text play a key role in collective evaluation processes.
