Hashtags are widely used for communication in online media. As a condensed version of information, they characterize topics and discussions. For their analysis, we apply methods from network science and propose novel tools for tracing their dynamics in time-dependent data. The observations are characterized by bursty behaviors in the increases and decreases of hashtag usage. These features can be reproduced with a novel model of dynamic rankings
peer-reviewedOnline social media has greatly affected the way in which we communicate with each othe...
The advent of the era of Big Data has allowed many researchers to dig into various socio-technical s...
Social media data are produced continuously by a large and uncontrolled number of users. The dynamic...
The dataset released here has been used in our paper "#Bigbirds Never Die: Understanding Social Dyna...
In light of the prosperity of online social media, Web users are shifting from data consumers to dat...
User generated information in online communities has been char-acterized with the mixture of a text ...
We examine the growth, survival, and context of 256 novel hashtags during the 2012 U.S. presidential...
The prevailing of Web 2.0 techniques has led to the boom of various online communities. Good exampl...
We draw a parallel between hashtag time series and neuron spike trains. In each case, the process pr...
Faster internet, IoT, and social media have reformed the conventional web into a collaborative web r...
Twitter is one of a popular microblogging site that allows registered user to engage and interact in...
Given the proliferation of social media and the abundance of news feeds, a substantial amount of rea...
Several previous approaches attempted to predict bursty topics on Twitter. Such approaches have usua...
Hashtags are used in Twitter to classify messages, propagate ideas and also to promote specific top...
As massive repositories of real-time human commentary, so-cial media platforms have arguably evolved...
peer-reviewedOnline social media has greatly affected the way in which we communicate with each othe...
The advent of the era of Big Data has allowed many researchers to dig into various socio-technical s...
Social media data are produced continuously by a large and uncontrolled number of users. The dynamic...
The dataset released here has been used in our paper "#Bigbirds Never Die: Understanding Social Dyna...
In light of the prosperity of online social media, Web users are shifting from data consumers to dat...
User generated information in online communities has been char-acterized with the mixture of a text ...
We examine the growth, survival, and context of 256 novel hashtags during the 2012 U.S. presidential...
The prevailing of Web 2.0 techniques has led to the boom of various online communities. Good exampl...
We draw a parallel between hashtag time series and neuron spike trains. In each case, the process pr...
Faster internet, IoT, and social media have reformed the conventional web into a collaborative web r...
Twitter is one of a popular microblogging site that allows registered user to engage and interact in...
Given the proliferation of social media and the abundance of news feeds, a substantial amount of rea...
Several previous approaches attempted to predict bursty topics on Twitter. Such approaches have usua...
Hashtags are used in Twitter to classify messages, propagate ideas and also to promote specific top...
As massive repositories of real-time human commentary, so-cial media platforms have arguably evolved...
peer-reviewedOnline social media has greatly affected the way in which we communicate with each othe...
The advent of the era of Big Data has allowed many researchers to dig into various socio-technical s...
Social media data are produced continuously by a large and uncontrolled number of users. The dynamic...