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

@inproceedings{Kwak2010WhatIT,
  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},
  year={2010}
}
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…

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References

SHOWING 1-10 OF 42 REFERENCES

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.

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.

Social Networks that Matter: Twitter Under the Microscope

A study of social interactions within Twitter reveals that the driver of usage is a sparse and hidden network of connections underlying the “declared” set of friends and followers.

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.

Worldwide Buzz: Planetary-Scale Views on an Instant-Messaging Network

A study of anonymized data capturing high-level communication activities within the Microsoft Instant Messenger network, which is the largest social network analyzed up to date, finds strong influences of homophily in activities, where people with similar characteristics overall tend to communicate more with one another.

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.