Topic-aware social influence propagation models
By Nicola Barbieri, Francesco Bonchi, Giuseppe Manco. Knowledge and Information Systems, 2012
420 citations recorded by the source corpus.
Subfields: Information Systems, Statistical and Nonlinear Physics
View Paper: https://www.semanticscholar.org/paper/3fc84367afbe5720750fb2af047ac899d9acc247
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In Information Systems
In Statistical and Nonlinear Physics
Citations in the corpus
- Dynamics of information diffusion and its applications on complex networks (2016, background): “, TIC model) [214], which involves items’ characteristics, users’ interests and social influence in the model.”
- Optimizing Ad Allocation in Social Advertising (2015, background): “Formally, a submodular function satisfies the follow property: For every X, Y ⊆ Ω with X ⊆ Y and every x ∈ Ω \ Y , we have that We say a submodular function f is monotone if f ( X ) ≤ f ( Y ) whenever X ⊆ Y .”
- Learning content–social influential features for influence analysis (2016, neutral): “[2] proposed topic-aware extensions of LT and IC models in influence maximization, and jointly considered user interests, authoritativeness and topic relevance to model influence propagation.”
- Influence Maximization on Social Graphs: A Survey (2018, methodology): “Inspired by topic-aware influence analysis [93], [94], recent studies [8], [76], [77], [78], [95] focus on IM for a topic-dependent diffusion model.”