A Decision Support System for Inbound Marketers: An Empirical Use of Latent Dirichlet Allocation Topic Model to Guide Infographic Designers

TL;DR

This paper presents a decision support system utilizing Latent Dirichlet Allocation to help infographic designers benchmark and improve their designs for increased virality, based on empirical analysis of past viral infographics.

Contribution

It introduces an empirical method that applies LDA topic modeling to guide infographic design decisions for inbound marketing.

Findings

Effective benchmarking of infographic designs against viral examples.

LDA-based analysis correlates design features with virality.

Guidance improves infographic success probability.

Abstract

Infographic is a type of information presentation that inbound marketers use. I suggest a method that can allow the infographic designers to benchmark their design against the previous viral infographics to measure whether a given design decision can help or hurt the probability of the design becoming viral.