What is Twitter, a social network or a news media?

By Haewoon Kwak, Changhyun Lee, Hosung Park, Sue B. Moon. 2010

7,204 citations recorded by the source corpus.

Subfields: Sociology and Political Science, Statistical and Nonlinear Physics

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Sociology and Political Science

In Statistical and Nonlinear Physics

Citations in the corpus

Political Communication and Influence through Microblogging--An Empirical Analysis of Sentiment in Twitter Messages and Retweet Behavior (2012, background): “[23] conducted a large-scale study to analyze the topological characteristics of Twitter and its power as a new medium of information sharing.”
Detection and Resolution of Rumours in Social Media (2017, background): “Social media platforms have shown great potential for news diffusion, occasionally even outpacing professional news outlets in breaking news reporting [Kwak et al. 2010].”
Scientists on Twitter: Preaching to the choir or singing from the rooftops? (2018, background): “So how can a scientist build and engage with their Twitter following? In general, people who tweet more have more followers (e.g., Huberman et al. 2008; Kwak et al. 2010).”
A Graph-Based Push Service Platform (2016, methodology): “In order to compare the efficiency of VENUS and PowerGraph, we ran experiments on twitter-graph [8], which contains 41,652,230 vertices and 1,468,364,884 edges.”
On the Interpretation of Digital Trace Data in Communication and Social Computing Research (2014, background): “, 2010; Castillo, Mendoza, & Poblete, 2011), and influence (Bakshy et al., 2011; Kwak et al., 2010).”
Computing Personalized PageRank Quickly by Exploiting Graph Structures (2014, background): “In addition, Twitter [31] has over 41 million users with 1.47 billion social interactions.”
Hip and trendy: Characterizing emerging trends on Twitter (2011, methodology): “…of our society (Johnson, 2009), as evidenced during major global events such as the Iran election or the reaction to the earthquake in Haiti (Kwak, Lee, Park, & Moon, 2010), as well as in response to local events and emergencies (Shklovski, Palen, & Sutton, 2008; Starbird, Palen, Hughes, &…”
Discovering users' topics of interest on twitter: a first look (2010, neutral): “Our approach leverages a knowledge base to disambiguate and categorize the entities in the Tweets.”
Recommender Systems (2012, background): “There are also indirect evidences about the positive social influences, for example, in Twitter, statistically a tweet will spread to about 10 3 users if it gets retweeted [238], and in Taobao, 11 the communication between buyers is a fundamental driving force for purchasing activity [239].”
Learning Semantic Relationships between Entities in Twitter (2011, background): “Research on temporal dynamics and information propagation on Twitter mostly focused on hashtags or observations of other sets of words in the tweets [16,17,11,20,3].”