Temporal trends in the interaction network formed using the public Twitter stream

Authors

  • Adrian Chester M. Balingit ⋅ PH National Institute of Physics, University of the Philippines Diliman
  • May T. Lim ⋅ PH National Institute of Physics, University of the Philippines Diliman

Abstract

Interaction networks from social networks such as Twitter reveal how users communicate with each other. Here we generate sampled interaction networks of users from the public Twitter stream starting from 2016, and measured their structure through maximum matching. We observed bimodality in the distribution of the unmatched node fraction. The bimodality reflects the presence of two distinct structures obtained from the interaction network when sampling, showing the sensitivity of the network to window sampling. With time, said bimodality started to occur at shorter sampling window sizes and hints at changes in interaction within the platform. It remains to be seen if the change occurs due to changes in user behavior, or is due to users responding to Twitter's algorithmic changes.

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Issue

Article ID

SPP-2022-3G-06

Section

Complex Systems and Data Analytics

Published

2022-10-04

How to Cite

[1]
ACM Balingit and MT Lim, Temporal trends in the interaction network formed using the public Twitter stream, Proceedings of the Samahang Pisika ng Pilipinas 40, SPP-2022-3G-06 (2022). URL: https://proceedings.spp-online.org/article/view/SPP-2022-3G-06.