<p>Tweet probability distribution, and the rankings of the popularity and the enhancement of key terms in Japanese tweets on (A) December 9, 2011 and (B) December 10, 2011. The collective attention in (A) was associated with the animated movie Castle in the Sky, whereas that in (B) was associated with a total lunar eclipse. The black bars in the figures indicate the time period when the posted tweets were analyzed to compute the term frequency. The red text in the tables indicates terms related to the target events and the text in parentheses shows the English translation.</p
<p>To conduct the experiment, we collect tweets from 4th to 16th March 2011: the period for the huge...
Quantifying public discourse is a topic of perennial interest in the social sciences. With the adven...
<p>We analyse tweets that are collected in the interval of one week before and after 11th March 2011...
<div><p></p><p>Online social media are increasingly facilitating our social interactions, thereby ma...
This dataset contains tweets ID posted before and after one week Tohoku Earthquake and iPhone 4 anno...
“Media events ” such as political debates generate conditions of shared attention as many users simu...
<p>(A) Distribution of number of tweets per user during the whole time span. The distribution follo...
Microblogging platforms such as Twitter have recently re-ceived much attention as great sources for ...
<div><p>“Media events” generate conditions of shared attention as many users simultaneously tune in ...
(a) The number and (b) the proportion of retweets that each influencer group accounted for out of th...
<p>The purpose of the investigation conducted was to discover trends in twitter popularity regarding...
<p>Tweet probability distribution for March 11, 2011, the day of the Tohoku-oki earthquake, showing ...
Frequency of tweets of the term “emergency” across the five disasters: a) Hurricane Irene; b) Hurric...
Frequency of tweets of the term “generator” across the five disasters: a) Hurricane Irene; b) Hurric...
Frequency of tweets of the term “supermarket” across the five disasters: a) Hurricane Irene; b) Hurr...
<p>To conduct the experiment, we collect tweets from 4th to 16th March 2011: the period for the huge...
Quantifying public discourse is a topic of perennial interest in the social sciences. With the adven...
<p>We analyse tweets that are collected in the interval of one week before and after 11th March 2011...
<div><p></p><p>Online social media are increasingly facilitating our social interactions, thereby ma...
This dataset contains tweets ID posted before and after one week Tohoku Earthquake and iPhone 4 anno...
“Media events ” such as political debates generate conditions of shared attention as many users simu...
<p>(A) Distribution of number of tweets per user during the whole time span. The distribution follo...
Microblogging platforms such as Twitter have recently re-ceived much attention as great sources for ...
<div><p>“Media events” generate conditions of shared attention as many users simultaneously tune in ...
(a) The number and (b) the proportion of retweets that each influencer group accounted for out of th...
<p>The purpose of the investigation conducted was to discover trends in twitter popularity regarding...
<p>Tweet probability distribution for March 11, 2011, the day of the Tohoku-oki earthquake, showing ...
Frequency of tweets of the term “emergency” across the five disasters: a) Hurricane Irene; b) Hurric...
Frequency of tweets of the term “generator” across the five disasters: a) Hurricane Irene; b) Hurric...
Frequency of tweets of the term “supermarket” across the five disasters: a) Hurricane Irene; b) Hurr...
<p>To conduct the experiment, we collect tweets from 4th to 16th March 2011: the period for the huge...
Quantifying public discourse is a topic of perennial interest in the social sciences. With the adven...
<p>We analyse tweets that are collected in the interval of one week before and after 11th March 2011...