Weng et al WSDM 10
This a Paper reviewed for Social Media Analysis 10-802 in Fall 2012.
Contents
Citation
author = {Jianshu Weng and
Ee-Peng Lim and
Jing Jiang and
Qi He},
title = {TwitterRank: finding topic-sensitive influential twitterers},
booktitle = {WSDM},
year = {2010},
pages = {261-270},
ee = {http://doi.acm.org/10.1145/1718487.1718520},
crossref = {DBLP:conf/wsdm/2010},
bibsource = {DBLP, http://dblp.uni-trier.de}
Online Version
TwitterRank: finding topic-sensitive influential twitterers
Summary
This primary goal of the work is to find influential users on Twitter website. The work proposes TwitterRank, a variation of Pagerank algorithm to measure influence of users in Twitter. TwitterRank takes into consideration the topical similarity between the users along with the link structure to measure influence of followers on users. The motive behind following a user and having mutual followers was studied to verify the presence of homophily in the network. The experimental results show that TwitterRank yields a significantly better result than the baseline techniques.
Dataset
The dataset consists of Singapore-based twitter users. The friends and followers network of top-1000 Singapore users is crawled along with their tweets. The dataset consists of number of tweets |T| = 1,021,039 and number of users |S| = 6748.
Methodology
- Homophily
In order to verify topical similarity in friendships, two question have been explored.
1. Whether users with "following" relationships are more topically similar than random users.
2. Whether users with reciprocal "following" relationships are more topically similar than those with it.
To answer the above questions, topics are extracted from the tweets of the user. Each user document is considered as the list of all the tweets by a user. The presence of homophily justifies the presence of topical similarities between users motivating the usage of TwitterRank.
Study Plan
Homophily
Related Papers
Homophily Paper
