The broad adoption of the web as a communication medium has made it possible
to study social behavior at a new scale. With social media networks such as
Twitter, we can collect large data sets of online discourse. Social science
researchers and journalists, however, may not have tools available to make
sense of large amounts of data or of the structure of large social networks. In
this paper, we describe our recent extensions to Truthy, a system for
collecting and analyzing political discourse on Twitter. We introduce several
new analytical perspectives on online discourse with the goal of facilitating
collaboration between individuals in the computational and social sciences. The
design decisions described in this article are motivated by real-world use
cases developed in collaboration with colleagues at the Indiana University
School of Journalism.
Description
Visualizing Communication on Social Media: Making Big Data Accessible
%0 Journal Article
%1 McKelvey2012
%A McKelvey, Karissa
%A Rudnick, Alex
%A Conover, Michael D.
%A Menczer, Filippo
%D 2012
%K communication media social visualizing
%T Visualizing Communication on Social Media: Making Big Data Accessible
%U http://arxiv.org/abs/1202.1367
%X The broad adoption of the web as a communication medium has made it possible
to study social behavior at a new scale. With social media networks such as
Twitter, we can collect large data sets of online discourse. Social science
researchers and journalists, however, may not have tools available to make
sense of large amounts of data or of the structure of large social networks. In
this paper, we describe our recent extensions to Truthy, a system for
collecting and analyzing political discourse on Twitter. We introduce several
new analytical perspectives on online discourse with the goal of facilitating
collaboration between individuals in the computational and social sciences. The
design decisions described in this article are motivated by real-world use
cases developed in collaboration with colleagues at the Indiana University
School of Journalism.
@article{McKelvey2012,
abstract = { The broad adoption of the web as a communication medium has made it possible
to study social behavior at a new scale. With social media networks such as
Twitter, we can collect large data sets of online discourse. Social science
researchers and journalists, however, may not have tools available to make
sense of large amounts of data or of the structure of large social networks. In
this paper, we describe our recent extensions to Truthy, a system for
collecting and analyzing political discourse on Twitter. We introduce several
new analytical perspectives on online discourse with the goal of facilitating
collaboration between individuals in the computational and social sciences. The
design decisions described in this article are motivated by real-world use
cases developed in collaboration with colleagues at the Indiana University
School of Journalism.
},
added-at = {2012-02-08T05:15:16.000+0100},
author = {McKelvey, Karissa and Rudnick, Alex and Conover, Michael D. and Menczer, Filippo},
biburl = {https://www.bibsonomy.org/bibtex/2e275f9f1a1ec14a2b391c6cd522b0ec7/kremplo},
description = {Visualizing Communication on Social Media: Making Big Data Accessible},
interhash = {ac6ad93f32034d2df35dbb9b5a77e478},
intrahash = {e275f9f1a1ec14a2b391c6cd522b0ec7},
keywords = {communication media social visualizing},
note = {cite arxiv:1202.1367},
timestamp = {2012-02-08T05:15:16.000+0100},
title = {Visualizing Communication on Social Media: Making Big Data Accessible},
url = {http://arxiv.org/abs/1202.1367},
year = 2012
}