Reply trees in Twitter: data analysis and branching process models

Abstract

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.

Modelling structure and predicting dynamics of discussion threads in online boards

“…The structure of so-called 'reply trees' was also studied by Nishi et. al in [21], where authors proposed simple principles for the formation of such trees. It is important to stress that the mechanisms behind retweet cascades and reply trees on one side, and discussion trees on the other side, are intrinsically different, due to the different designs of their platforms.…”

Generative models of online discussion threads: state of the art and research challenges

“…• Kumar et al [83] • Wang et al [84], • Gómez et al [85] • Backstrom et al [86] • Nishi et al [87] • Lumbreras [88] • Aragón et al [89] The selection of these models is based on the consideration of Kumar et al [83] as the first generative model for online discussion threads. The rest of the models in the survey were selected after examining the publications citing this work in Scopus (52 papers) and Google Scholar (92 papers) 2 , and including the studies which proposed a generative model for the structure and growth of online discussion threads.…”

A Hierarchical Model of Nonhomogeneous Poisson Processes for Twitter Retweets

“…It is also possible to model network structure and information diffusion simultaneously without using time as a dimension. Both Li et al (2012) and Nishi et al (2016) use a Galton-Watson branching process model, for data of video contents shared on online social networks, and reply trees in Twitter, respectively.…”