Reply trees in Twitter: data analysis and branching process models

Ryosuke Nishi, Taro Takaguchi*, Keigo Oka, Takanori Maehara, Masashi Toyoda, Ken ichi Kawarabayashi, Naoki Masuda

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

38 Citations (Scopus)


Structure of networks constructed from mentioning relationships between posts in online media may be valuable for understanding how information and opinions spread in these media. We crawled Twitter to collect tweets and replies to construct a large number of so-called reply trees, each of which was rooted at a tweet and joined by replies. Consistent with the previous literature, we found that the empirical trees were characterized by some long path-like reply trees, large star-like trees, and long irregular trees, although their frequencies were not high. We tested several branching process models to explain the empirical frequency of these types of reply trees as well as more basic quantities such as the distributions of the size and depth of the reply tree. Based on our modeling results, we suggest that the in-degree of the tweet that initiates a reply tree (i.e., the number of times that the tweet is directly mentioned by other reply posts) may play an important role in forming the global shape of the reply tree.

Original languageEnglish
Article number26
JournalSocial Network Analysis and Mining
Issue number1
Publication statusPublished - 2016 Dec 1
Externally publishedYes


  • Branching process
  • Data analysis
  • Reply tree
  • Twitter

ASJC Scopus subject areas

  • Information Systems
  • Communication
  • Media Technology
  • Human-Computer Interaction
  • Computer Science Applications


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