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Contraction of Online Response to Major Events

Figure 3

Distributions of individual activity features and their timelines.

(A) Distribution of number of tweets per user during the whole time span. The distribution follows approximately a power law with slope . (B) Cumulative distribution of absolute thresholds of all users, i.e. the smallest hourly volume for each user in which a tweet is posted. Approximately of users only post during the one hour which marks the final of the event, but roughly one fourth of the users also post during hours in which less than 1000 tweets are posted. (C) Participation thresholds over time ( is measured separately for each user over the whole timespan; for each hour we average the values of all unique users who tweet in that hour). The curve follows roughly the volume curve of , showing that high volume phases feature additional users who only post during those phases. (D) Timeline of number of tweets per unique user , . During the event, each user posts on average around tweets per hour, with a particular peak at the finale of the tournament, showing that single users write slightly more messages during that time of high excitation. After the event, the individual activity increases slightly due to the departure of the masses of casual Twitter users.

Figure 3

doi: https://doi.org/10.1371/journal.pone.0089052.g003