Twitterrank: Finding topic-sensitive influential Twitterers

This paper focuses on the problem of identifying influential users of micro-blogging services. Twitter, one of the most notable micro-blogging services, employs a social-networking model called "following", in which each user can choose who she wants to "follow" to receive tweets...

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Main Authors: WENG, Jianshu, LIM, Ee Peng, JIANG, Jing, HE, Qi
Format: text
Language:English
Published: Institutional Knowledge at Singapore Management University 2010
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Online Access:https://ink.library.smu.edu.sg/sis_research/504
https://ink.library.smu.edu.sg/context/sis_research/article/1503/viewcontent/p261_weng.pdf
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spelling sg-smu-ink.sis_research-15032018-06-20T03:35:01Z Twitterrank: Finding topic-sensitive influential Twitterers WENG, Jianshu LIM, Ee Peng JIANG, Jing HE, Qi This paper focuses on the problem of identifying influential users of micro-blogging services. Twitter, one of the most notable micro-blogging services, employs a social-networking model called "following", in which each user can choose who she wants to "follow" to receive tweets from without requiring the latter to give permission first. In a dataset prepared for this study, it is observed that (1) 72.4% of the users in Twitter follow more than 80% of their followers, and (2) 80.5% of the users have 80% of users they are following follow them back. Our study reveals that the presence of "reciprocity" can be explained by phenomenon of homophily. Based on this finding, TwitterRank, an extension of PageRank algorithm, is proposed to measure the influence of users in Twitter. TwitterRank measures the influence taking both the topical similarity between users and the link structure into account. Experimental results show that TwitterRank outperforms the one Twitter currently uses and other related algorithms, including the original PageRank and Topic-sensitive PageRank. 2010-02-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/504 info:doi/10.1145/1718487.1718520 https://ink.library.smu.edu.sg/context/sis_research/article/1503/viewcontent/p261_weng.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Influence Pagerank Twitter Microblogging Reciprocity Databases and Information Systems Numerical Analysis and Scientific Computing Social Media
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Influence
Pagerank
Twitter
Microblogging
Reciprocity
Databases and Information Systems
Numerical Analysis and Scientific Computing
Social Media
spellingShingle Influence
Pagerank
Twitter
Microblogging
Reciprocity
Databases and Information Systems
Numerical Analysis and Scientific Computing
Social Media
WENG, Jianshu
LIM, Ee Peng
JIANG, Jing
HE, Qi
Twitterrank: Finding topic-sensitive influential Twitterers
description This paper focuses on the problem of identifying influential users of micro-blogging services. Twitter, one of the most notable micro-blogging services, employs a social-networking model called "following", in which each user can choose who she wants to "follow" to receive tweets from without requiring the latter to give permission first. In a dataset prepared for this study, it is observed that (1) 72.4% of the users in Twitter follow more than 80% of their followers, and (2) 80.5% of the users have 80% of users they are following follow them back. Our study reveals that the presence of "reciprocity" can be explained by phenomenon of homophily. Based on this finding, TwitterRank, an extension of PageRank algorithm, is proposed to measure the influence of users in Twitter. TwitterRank measures the influence taking both the topical similarity between users and the link structure into account. Experimental results show that TwitterRank outperforms the one Twitter currently uses and other related algorithms, including the original PageRank and Topic-sensitive PageRank.
format text
author WENG, Jianshu
LIM, Ee Peng
JIANG, Jing
HE, Qi
author_facet WENG, Jianshu
LIM, Ee Peng
JIANG, Jing
HE, Qi
author_sort WENG, Jianshu
title Twitterrank: Finding topic-sensitive influential Twitterers
title_short Twitterrank: Finding topic-sensitive influential Twitterers
title_full Twitterrank: Finding topic-sensitive influential Twitterers
title_fullStr Twitterrank: Finding topic-sensitive influential Twitterers
title_full_unstemmed Twitterrank: Finding topic-sensitive influential Twitterers
title_sort twitterrank: finding topic-sensitive influential twitterers
publisher Institutional Knowledge at Singapore Management University
publishDate 2010
url https://ink.library.smu.edu.sg/sis_research/504
https://ink.library.smu.edu.sg/context/sis_research/article/1503/viewcontent/p261_weng.pdf
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