Chain-sense signature of the Twitter interaction network during the 2016−2022 period

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

Measuring the structure of interaction networks through time allows for studying when and how changes in the behavior of a social network platform and its users occur. Here, we use chain-sense, which can be roughly described as a way to describe the linearity of interactions, to measure and describe the interaction network sampled from the Twitter public stream API from 2016 to 2022. We compare the measurements before and after 2020, which marked the start of lockdowns due to COVID-19 and the increase in internet activity. The chain-sense signature post-2020 indicate a bimodality different from those observed prior.

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Issue

Entangled!
25-28 June 2025, National Institute of Physics, University of the Philippines Diliman

Please visit the SPP2025 activity webpage for more information on this year's Physics Congress.

Article ID

SPP-2025-2G-03

Section

Complex Systems and Data Analytics

Published

2025-06-19

How to Cite

[1]
ACM Balingit and MT Lim, Chain-sense signature of the Twitter interaction network during the 2016−2022 period, Proceedings of the Samahang Pisika ng Pilipinas 43, SPP-2025-2G-03 (2025). URL: https://proceedings.spp-online.org/article/view/SPP-2025-2G-03.