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Dataset . 2015
License: CC 0
Data sources: ZENODO
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Following/Followers and Tags on 0.1 million Twitter Users

Authors: Yoshida, Mitsuo; Yamaguchi, Yuto;

Following/Followers and Tags on 0.1 million Twitter Users

Abstract

Abstract (our paper) Why does Smith follow Johnson on Twitter? In most cases, the reason why users follow other users is unavailable. In this work, we answer this question by proposing TagF, which analyzes the who-follows-whom network (matrix) and the who-tags-whom network (tensor) simultaneously. Concretely, our method decomposes a coupled tensor constructed from these matrix and tensor. The experimental results on million-scale Twitter networks show that TagF uncovers different, but explainable reasons why users follow other users. Data coupled_tensor: The first column is the source user id (from user id), the second column is the destination user id (to user id), and the third column is the tag id. users.id: The first column is the user id for coupled_tensor, and the second column is the user id on Twitter. tags.id: The first column is the tag id for coupled_tensor, and the second column is the tag (i.e. slug or list name) on Twitter. On the tags, ###follow### and ###friend### are special tags expressing follower and following. Publication This dataset was created for our study. If you make use of this dataset, please cite: Yuto Yamaguchi, Mitsuo Yoshida, Christos Faloutsos, Hiroyuki Kitagawa. Why Do You Follow Him? Multilinear Analysis on Twitter. Proceedings of the 24th International Conference on World Wide Web (WWW '15 Companion). pp.137-138, 2015. http://doi.org/10.1145/2740908.2742715 Code Our code outputting experiment results made available at: https://github.com/yamaguchiyuto/tagf Note If you would like to use larger dataset, the dataset on 1 million seed users made available at: http://dx.doi.org/10.5281/zenodo.16267 (The dataset on 0.1 million seed users is not subset of the dataset on 1 million seed users.)

Subjects by Vocabulary

EOSC: Twitter Data

Keywords

Twitter, Tensor Analysis, Social Tagging, Social Graph

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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views
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