For a deep dive, why not excavate the references in the ANU Computational Media Group which does an excellent job in this realm?
Achab, Massil, Emmanuel Bacry, Stéphane Gaïffas, Iacopo Mastromatteo, and Jean-Francois Muzy. 2017. “Uncovering Causality from Multivariate Hawkes Integrated Cumulants.” In PMLR. http://arxiv.org/abs/1607.06333.
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Broniatowski, David A., Amelia M. Jamison, SiHua Qi, Lulwah AlKulaib, Tao Chen, Adrian Benton, Sandra C. Quinn, and Mark Dredze. 2018. “Weaponized Health Communication: Twitter Bots and Russian Trolls Amplify the Vaccine Debate.” American Journal of Public Health 108 (10): 1378–84. https://doi.org/10.2105/AJPH.2018.304567.
Dodds, Peter Sheridan. 2017. “Slightly Generalized Generalized Contagion: Unifying Simple Models of Biological and Social Spreading.” August 31, 2017. http://arxiv.org/abs/1708.09697.
Du, Nan, Hanjun Dai, Rakshit Trivedi, Utkarsh Upadhyay, Manuel Gomez-Rodriguez, and Le Song. 2016. “Recurrent Marked Temporal Point Processes: Embedding Event History to Vector.” In Proceedings of the 22Nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, 1555–64. KDD ’16. New York, NY, USA: ACM. https://doi.org/10.1145/2939672.2939875.
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Du, Nan, Le Song, Ming Yuan, and Alex J. Smola. 2012. “Learning Networks of Heterogeneous Influence.” In Advances in Neural Information Processing Systems, 2780–88. http://papers.nips.cc/paper/4582-learning-networks-of-heterogeneous-influence.
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Gomez-Rodriguez, Manuel, Jure Leskovec, and Bernhard Schölkopf. 2013. “Structure and Dynamics of Information Pathways in Online Media.” In Proceedings of the Sixth ACM International Conference on Web Search and Data Mining, 23–32. WSDM ’13. New York, NY, USA: ACM. https://doi.org/10.1145/2433396.2433402.
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Jakesch, Maurice, Kiran Garimella, Dean Eckles, and Mor Naaman. 2021. “#Trend Alert: How a Cross-Platform Organization Manipulated Twitter Trends in the Indian General Election.” April 27, 2021. http://arxiv.org/abs/2104.13259.
Khim, Justin, Varun Jog, and Po-Ling Loh. 2016. “Computationally Efficient Influence Maximization in Stochastic and Adversarial Models: Algorithms and Analysis.” November 1, 2016. http://arxiv.org/abs/1611.00350.
Kim, Minkyoung, Lexing Xie, and Peter Christen. n.d. “Event Diffusion Patterns in Social Media,” 8.
Kong, Quyu, Marian-Andrei Rizoiu, Siqi Wu, and Lexing Xie. 2018. “Will This Video Go Viral? Explaining and Predicting the Popularity of Youtube Videos.” Companion of the The Web Conference 2018 on The Web Conference 2018 - WWW ’18, 175–78. https://doi.org/10.1145/3184558.3186972.
Kong, Quyu, Marian-Andrei Rizoiu, and Lexing Xie. 2020. “Modeling Information Cascades with Self-Exciting Processes via Generalized Epidemic Models.” In Proceedings of the 13th International Conference on Web Search and Data Mining, 286–94. WSDM ’20. New York, NY, USA: Association for Computing Machinery. https://doi.org/10.1145/3336191.3371821.
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Rizoiu, Marian-Andrei, Timothy Graham, Rui Zhang, Yifei Zhang, Robert Ackland, and Lexing Xie. 2018. “#DebateNight: The Role and Influence of Socialbots on Twitter During the 1st 2016 U.S. Presidential Debate.” May 16, 2018. http://arxiv.org/abs/1802.09808.
Rizoiu, Marian-Andrei, Swapnil Mishra, Quyu Kong, Mark Carman, and Lexing Xie. 2018. “SIR-Hawkes: Linking Epidemic Models and Hawkes Processes to Model Diffusions in Finite Populations.” In Proceedings of the 2018 World Wide Web Conference, 419–28. Republic and Canton of Geneva, CHE: International World Wide Web Conferences Steering Committee. https://doi.org/10.1145/3178876.3186108.
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Wu, Siqi, Marian-Andrei Rizoiu, and Lexing Xie. 2019. “Estimating Attention Flow in Online Video Networks.” Proceedings of the ACM on Human-Computer Interaction 3 (November): 1–25. https://doi.org/10.1145/3359285.
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