Modeling information diffusion in online social networks using a modified forest-fire model
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Modeling information diffusion in online social networks using a modified forest-fire model Sanjay Kumar1,2
· Muskan Saini3 · Muskan Goel4 · B. S. Panda2
Received: 12 July 2020 / Revised: 22 September 2020 / Accepted: 22 September 2020 / © Springer Science+Business Media, LLC, part of Springer Nature 2020
Abstract Information dissemination has changed rapidly in recent years with the emergence of social media which provides online platforms for people worldwide to share their thoughts, activities, emotions, and build social relationships. Hence, modeling information diffusion has become an important area of research in the field of network analysis. It involves the mathematical modeling of the movement of information and study the information spread pattern. In this paper, we attempt to model information propagation in online social networks using a nature-inspired approach based on a modified forest-fire model. A slight spark can start a wildfire in a forest, and the spread of this fire depends on vegetation, weather, and topography, which may act as fuel. On similar lines, we labeled users who haven’t joined the network yet as Empty, existing users as T ree, and information as F ire. The spread of information across online social networks depends upon users-followers relationships, the significance of the topic, and other such features. We introduce a novel Burnt state to the traditional forest-fire model to represent non-spreaders in the network. We validate our method on six real-world data-sets extracted from Twitter and conclude that the proposed model performs reasonably well in predicting information diffusion. Keywords Information diffusion · Forest-fire model · Nature-inspired algorithm · Online social networks · Twitter
1 Introduction Many complex systems like biological, communication and social networks can be modeled as graphs (Newman 2010). These systems constitute a large number of nodes with a complicated interaction among its members (Wang et al. 2012; Barab´asi 2016). Social networks are online resources that link people and help in the spread of information (Bakshy et al. 2012). Due to the rapid advancements of the internet and mobile networks, online Sanjay Kumar
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Extended author information available on the last page of the article.
Journal of Intelligent Information Systems
social networks (OSNs) like Twitter, Facebook, Siena Weibo have become very popular and connects billions of people worldwide. These platforms excel as tools for people to share news, trending topics, ideas, and opinions. Hence, online social networks have brought people together, enhance communication speed and generate a massive amount of data in a few minutes. Some actions of a few numbers of people may lead to a large scale spreading of information. It takes only a few clicks for information to reach from one corner of the world to another. Twitter, a micro-blogging website is one such network. As compared to other networks, Twitter is more diverse and densely connected. These properties m
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