Modeling information diffusion in social media: data-driven observations

Frontiers in Big Data

Big Data

Adriana Iamnitchi¹  Kin Wai Ng²  Frederick Mubang²  Sameera Horawalavithana²  Lawrence O. Hall²  John Skvoretz³ 

[1] Department of Advanced Computing Sciences, Institute of Data Science, Maastricht University, Maastricht, Netherlands;Department of Computer Science and Engineering, University of South Florida, Tampa, FL, United States;Department of Computer Science and Engineering, University of South Florida, Tampa, FL, United States;Department of Sociology, University of South Florida, Tampa, FL, United States;

关键词: social media;    forecasting;    data-driven;    Twitter;    Reddit;    YouTube;   

DOI  :  10.3389/fdata.2023.1135191

 received in 2022-12-31, accepted in 2023-04-24,  发布年份 2023

来源: Frontiers

【 摘 要 】

Accurately modeling information diffusion within and across social media platforms has many practical applications, such as estimating the size of the audience exposed to a particular narrative or testing intervention techniques for addressing misinformation. However, it turns out that real data reveal phenomena that pose significant challenges to modeling: events in the physical world affect in varying ways conversations on different social media platforms; coordinated influence campaigns may swing discussions in unexpected directions; a platform's algorithms direct who sees which message, which affects in opaque ways how information spreads. This article describes our research efforts in the SocialSim program of the Defense Advanced Research Projects Agency. As formulated by DARPA, the intent of the SocialSim research program was “to develop innovative technologies for high-fidelity computational simulation of online social behavior ... [focused] specifically on information spread and evolution.” In this article we document lessons we learned over the 4+ years of the recently concluded project. Our hope is that an accounting of our experience may prove useful to other researchers should they attempt a related project.

【 授权许可】

Unknown   
Copyright © 2023 Iamnitchi, Hall, Horawalavithana, Mubang, Ng and Skvoretz.