research-article

Exploring Twitter networks in parallel computing environments

Authors:

Bo Xu,

Yun Huang,

Noshir ContractorAuthors Info & Claims

XSEDE '13: Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery

Article No.: 20, Pages 1 - 5

https://doi.org/10.1145/2484762.2484811

Published: 22 July 2013 Publication History

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Abstract

Millions of users follow each other on Twitter and form a large and complex network. The size of the network creates statistical and computational challenges on exploring and examining individual behavior on Twitter. Using a sample of 697,628 Korean Twitter users and 34 million relations, this study investigates the patterns of unfollow behavior on Twitter, i.e. people removing others from their Twitter follow lists. We use Exponential Random Graph Models (p*/ERGMs) and Statnet in R to examine the impacts of reciprocity, status, embeddedness, homophily, and informativeness on tie dissolution. We perform data processing, statistics calculation, network sampling, and Markov chain Monte Carlo (MCMC) simulation on Gordon, a unique supercomputer at the San Diego Supercomputer Center (SDSC). The process demonstrates the role of advanced computing technologies in social science studies.

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Cited By

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Yoshida MSakaki TKobayashi TToriumi F(2021)Japanese conservative messages propagate to moderate users better than their liberal counterparts on TwitterScientific Reports10.1038/s41598-021-98349-211:1Online publication date: 4-Oct-2021
https://doi.org/10.1038/s41598-021-98349-2

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Exploring Twitter networks in parallel computing environments
1. Human-centered computing

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XSEDE '13: Proceedings of the Conference on Extreme Science and Engineering Discovery Environment: Gateway to Discovery

July 2013

433 pages

ISBN:9781450321709

DOI:10.1145/2484762

General Chair:
Nancy Wilkins-Diehr
San Diego Supercomputer Center

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Association for Computing Machinery

New York, NY, United States

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Published: 22 July 2013

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XSEDE '13

XSEDE '13: Extreme Science and Engineering Discovery Environment: Gateway to Discovery

July 22 - 25, 2013

California, San Diego, USA

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Yoshida MSakaki TKobayashi TToriumi F(2021)Japanese conservative messages propagate to moderate users better than their liberal counterparts on TwitterScientific Reports10.1038/s41598-021-98349-211:1Online publication date: 4-Oct-2021
https://doi.org/10.1038/s41598-021-98349-2

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Measuring influence on Twitter

Finding news-topic oriented influential twitter users based on topic related hashtag community detection

A sentiment analysis of audiences on twitter: who is the positive or negative audience of popular twitterers?

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Measuring influence on Twitter

Finding news-topic oriented influential twitter users based on topic related hashtag community detection

A sentiment analysis of audiences on twitter: who is the positive or negative audience of popular twitterers?

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