@inproceedings{135ee8f3e4df4be2adfd3bb8ddddfacf,
title = "Time critical disinformation influence minimization in online social networks",
abstract = "If a piece of disinformation released from a terrorist organization propagates on Twitter and this adversarial campaign is detected after a while, how emergence responders can wisely choose a set of source users to start the counter campaign to minimize the disruptive influence of disinformation in a short time This practical problem is challenging and critical for authorities to make online social networks a more trustworthy source of information. In this work, we propose to study the time critical disinformation influence minimization problem in online social networks based on a continuous-time multiple campaign diffusion model. We show that the complexity of this optimization problem is NP-hard and provide a provable guaranteed approximation algorithm for this problem by proving several critical properties of the objective function. Experimental results on a sample of real online social network show that the proposed approximation algorithm outperforms various heuristics and the transmission temporal dynamics knowledge is vital for selecting the counter campaign source users, especially when the time window is small.",
keywords = "competing campaigns, disinformation, information cascades, social networks, submodular functions",
author = "Chuan Luo and Kainan Cui and Xiaolong Zheng and Daniel Zeng",
year = "2014",
month = dec,
day = "4",
doi = "10.1109/JISIC.2014.20",
language = "English (US)",
series = "Proceedings - 2014 IEEE Joint Intelligence and Security Informatics Conference, JISIC 2014",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "68--74",
booktitle = "Proceedings - 2014 IEEE Joint Intelligence and Security Informatics Conference, JISIC 2014",
note = "2014 IEEE Joint Intelligence and Security Informatics Conference, JISIC 2014 ; Conference date: 24-09-2014 Through 26-09-2014",
}