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

  title={What is Twitter, a social network or a news media?},
  author={Haewoon Kwak and Changhyun Lee and Hosung Park and Sue B. Moon},
  booktitle={The Web Conference},
Twitter, a microblogging service less than three years old, commands more than 41 million users as of July 2009 and is growing fast. [] Key Result In order to identify influentials on Twitter, we have ranked users by the number of followers and by PageRank and found two rankings to be similar. Ranking by retweets differs from the previous two rankings, indicating a gap in influence inferred from the number of followers and that from the popularity of one's tweets. We have analyzed the tweets of top trending…

Topics and Influential User Identification in Twitter using Twitter Lists

By analyzing Twitter List, this paper is able to detect topics and identify influential users in the corresponding topic more efficiently and, on an experimental evaluation, the influential users identified by the proposed method have the average influence score related to the topic made by interviewees.

Characterization of the twitter @replies network: are user ties social or topical?

It is found that the social aspect predominantly conditions users' interactions, and for users with larger and denser ego-centric networks, there is a slight tendency for separating their connections depending on the topics discussed.

A study on Twitter user-follower network a network based analysis

The investigations showed that the Twitter user-follower network follows power-law degree distribution and was found to be a connected network, which yields to friend recommendations, target based advertisements, etc.

Towards scalable X10 based link prediction for large scale social networks

This research implemented one of the link prediction algorithm named Link Propagation in X10, which is a parallel programming language, and evaluated its scalability and precision with Twitter user network data.

Quantifying Influence in Social Networks and News Media

  • Hong-Won Yun
  • Computer Science
    J. Inform. and Commun. Convergence Engineering
  • 2012
This work chose Twitter and the New York Times as representative media to analyze the influence and present an empirical analysis of these datasets, and measures the normalized influence score using the proposed expression based on the two correlation coefficients.

Estimating the Spreading of Viral Threads on Twitter

This model is based on the hypothesis that it is highly probable that a user decides to retweet a tweet if he/she is following either the tweet author, or another retweeter of the tweet, and chooses as main features of a tweet its number of retweets and the number of followers of retweeting users.

Finding Influential Users and Popular Contents on Twitter

A novel random walk model was proposed to measure the users’ influence and tweets’ popularity and results show that this method is consistently better than PageRank method with the network of following and the method of retweetNum which measures the popularity of contents according to the number of retweets.

Information Propagation Speed and Patterns in Social Networks: A Case Study Analysis of German Tweets

The analysis has shown that information diffuses over time through the Twitter network in certain patterns, and it has shown those friend relationships significantly influence the information propagation speed on Twitter.

TRank: Ranking Twitter users according to specific topics

  • M. MontangeroM. Furini
  • Computer Science
    2015 12th Annual IEEE Consumer Communications and Networking Conference (CCNC)
  • 2015
This paper proposes TRank, a novel method designed to address the problem of identifying the most influential Twitter users on specific topics identified with hashtags that combines different Twitter signals to provide three different indicators that are intended to capture different aspects of being influent.



TwitterRank: finding topic-sensitive influential twitterers

Experimental results show that TwitterRank outperforms the one Twitter currently uses and other related algorithms, including the original PageRank and Topic-sensitive PageRank, which is proposed to measure the influence of users in Twitter.

Why we twitter: understanding microblogging usage and communities

It is found that people use microblogging to talk about their daily activities and to seek or share information and the user intentions associated at a community level are analyzed to show how users with similar intentions connect with each other.

Analysis of topological characteristics of huge online social networking services

Cyworld, MySpace, and orkut, each with more than 10 million users, are compared and it is shown that they deviate from close-knit online social networks which show a similar degree correlation pattern to real-life social networks.

A measurement-driven analysis of information propagation in the flickr social network

Analysis of large-scale traces of information dissemination in the Flickr social network finds that even popular photos do not spread widely throughout the network, and the role of word-of-mouth exchanges between friends in the overall propagation of information in the network is questioned.

Characterizing user behavior in online social networks

A first of a kind analysis of user workloads in online social networks, based on detailed clickstream data collected over a 12-day period, shows that browsing, which cannot be inferred from crawling publicly available data, accounts for 92% of all user activities.

Planetary-scale views on a large instant-messaging network

It is found that people tend to communicate more with each other when they have similar age, language, and location, and that cross-gender conversations are both more frequent and of longer duration than conversations with the same gender.

A few chirps about twitter

A detailed characterization of Twitter, an application that allows users to send short messages, is presented, which identifies distinct classes of Twitter users and their behaviors, geographic growth patterns and current size of the network.

User interactions in social networks and their implications

This paper proposes the use of interaction graphs to impart meaning to online social links by quantifying user interactions, and uses both types of graphs to validate two well-known social-based applications (RE and SybilGuard).

Comparison of online social relations in volume vs interaction: a case study of cyworld

The first attempt to compare the explicit friend relationship network and implicit activity network is compared and it is reported that the in-degree and out-degree distributions are close to each other and the social interaction through the guestbook is highly reciprocated.

Gesundheit! Modeling Contagion through Facebook News Feed

An analysis of Facebook diffusion chains using zero-inflated negative binomial regressions shows that after controlling for distribution effects, there is no meaningful evidence that a start node’s maximum diffusion chain length can be predicted with the user's demographics or Facebook usage characteristics.