Information Interaction Profile of Choice Adoption

by   Gaël Poux-Médard, et al.

Interactions between pieces of information (entities) play a substantial role in the way an individual acts on them: adoption of a product, the spread of news, strategy choice, etc. However, the underlying interaction mechanisms are often unknown and have been little explored in the literature. We introduce an efficient method to infer both the entities interaction network and its evolution according to the temporal distance separating interacting entities; together, they form the interaction profile. The interaction profile allows characterizing the mechanisms of the interaction processes. We approach this problem via a convex model based on recent advances in multi-kernel inference. We consider an ordered sequence of exposures to entities (URL, ads, situations) and the actions the user exerts on them (share, click, decision). We study how users exhibit different behaviors according to combinations of exposures they have been exposed to. We show that the effect of a combination of exposures on a user is more than the sum of each exposure's independent effect–there is an interaction. We reduce this modeling to a non-parametric convex optimization problem that can be solved in parallel. Our method recovers state-of-the-art results on interaction processes on three real-world datasets and outperforms baselines in the inference of the underlying data generation mechanisms. Finally, we show that interaction profiles can be visualized intuitively, easing the interpretation of the model.



There are no comments yet.


page 1

page 2

page 3

page 4


Referring Expression Generation Using Entity Profiles

Referring Expression Generation (REG) is the task of generating contextu...

Relation-aware Heterogeneous Graph for User Profiling

User profiling has long been an important problem that investigates user...

Interactions in information spread: quantification and interpretation using stochastic block models

In most real-world applications, it is seldom the case that a given obse...

Data-driven discovery of interacting particle systems using Gaussian processes

Interacting particle or agent systems that display a rich variety of col...

Towards Interaction Detection Using Topological Analysis on Neural Networks

Detecting statistical interactions between input features is a crucial a...

SocialInteractionGAN: Multi-person Interaction Sequence Generation

Prediction of human actions in social interactions has important applica...

aiTPR: Attribute Interaction-Tensor Product Representation for Image Caption

Region visual features enhance the generative capability of the machines...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.