  With an increasing outreach of digital platforms in our lives, researchers
have taken a keen interest to study different facets of social interactions
that seem to be evolving rapidly. Analysing the spread of information (aka
diffusion) has brought forth multiple research areas such as modelling user
engagement, determining emerging topics, forecasting virality of online posts
and predicting information cascades. Despite such ever-increasing interest,
there remains a vacuum among easy-to-use interfaces for large-scale
visualisation of diffusion models. In this paper, we introduce DiVA --
Diffusion Visualisation and Analysis, a tool that provides a scalable web
interface and extendable APIs to analyse various diffusion trends on networks.
DiVA uniquely offers support for simultaneous comparison of two competing
diffusion models and even the comparison with the ground-truth results, both of
which help develop a coherent understanding of real-world scenarios. Along with
performing an exhaustive feature comparison and system evaluation of DiVA
against publicly-available web interfaces for information diffusion, we
conducted a user study to understand the strengths and limitations of DiVA. We
noticed that evaluators had a seamless user experience, especially when
analysing diffusion on large networks.
