CyNetDiff Submission

[eliotwrobson]

Submitting Author: Name (@eliotwrobson)
All current maintainers: (@eliotwrobson, @abhishekumrawal)
Package Name: CyNetDiff
One-Line Description of Package: A performance-focused library implementing algorithms for simulating network diffusion processes, written in Cython.
Repository Link: https://github.com/eliotwrobson/CyNetDiff
Version submitted: v0.1.13
EIC: @Batalex
Editor: @sneakers-the-rat
Reviewer 1: TBD
Reviewer 2: TBD
Archive: TBD
JOSS DOI: TBD
Version accepted: TBD
Date accepted (month/day/year): TBD

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Network diffusion processes aim to model the spread of information through social networks, represented using graphs. Experimental work involving these models usually involves simulating these processes many times over large graphs, which can be computationally very expensive. At the same time, being able to conduct experiments using a high-level language like Python is helpful to researchers, as this gives greater flexibility in developing research software. To address both of these concerns, CyNetDiff is a Cython module implementing the independent cascade and linear threshold models, two of the most popular network diffusion models. Development has been focused on performance, while still giving an intuitive, high-level interface to assist in research tasks.

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This is aimed at researchers working in areas related to network diffusion and influence maximization, and specifically at optimizing the most computationally expensive part of this process. This should enable researchers to conduct experiments on larger graphs than would be possible with a pure-Python package. For a recent work doing experiments that fit the use cases of this package, see https://arxiv.org/abs/2207.08937

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There is a previous package filling a similar use case called ndlib: https://github.com/GiulioRossetti/ndlib
Our package differs as it was developed with a focus on performance, and with lesser emphasis on visualization
and flexibility (for example, we do not have a way of defining custom models). Using code compiled with Cython
allows our package to handle much larger graphs than are possible with a pure-Python package like ndlib.

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#165, @Batalex

Continuing off of the discussion there, the main goals of the review for me are to finalize the interface and add related features / utility code to aid usability. In terms of concrete features, the algorithms already implemented are enough for a full release.

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[Batalex]

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Editor comments

I think the documentation is a little bare currently to get started with the review. I'd like to see the information you wrote in this submission issue in the project repository itself. For example:

Network diffusion processes aim to model the spread of information through social networks, represented using graphs. Experimental work involving these models usually involves simulating these processes many times over large graphs, which can be computationally very expensive. At the same time, being able to conduct experiments using a high-level language like Python is helpful to researchers, as this gives greater flexibility in developing research software. To address both of these concerns, CyNetDiff is a Cython module implementing the independent cascade and linear threshold models, two of the most popular network diffusion models. Development has been focused on performance, while still giving an intuitive, high-level interface to assist in research tasks.

This is a nice elevator pitch to rework and include in the README.

I'd like to see more content in the documentation as well. The API section is great, but the basic example lacks context and does not really show case what CyNetDiff is great for. I want to share with you this resource: Diátaxis framework.
I am not asking that you follow the full framework to the letter, and it would be a huge task to do so, but I think there is some virtue in thinking about the kind of documentation you aim to showcase.
The documentation is the first thing a potential user will take a look at. As such, it needs to quickly guide the reader to:

• what does it do? (= should I try it?)
• how does it work? (= ok, I think this is the tool I need, how do I proceed?)

[eliotwrobson]

Thank you for the feedback! I think those changes are reasonable and will significantly enhance the package, I'll try and expand the documentation by Monday so we can get the ball rolling on the review before too long 🚀

[eliotwrobson]

@Batalex I have just published a release with the following changes:

• Updated the elevator pitch and example in the README
• Added two longer extended examples to the documentation site

[Batalex]

Thanks, this looks great. From what I can tell, we are good to go. I'll get started on finding the perfect editor for this review 🐈‍⬛

[eliotwrobson]

@Batalex I know we don't have an editor yet, but is it too early to begin suggesting reviewers? We've already found someone that might be a good candidate for this.

[Batalex]

@Batalex I know we don't have an editor yet, but is it too early to begin suggesting reviewers? We've already found someone that might be a good candidate for this.

That's fantastic!
Could you please orient them to our signups form? https://forms.gle/GHfxvmS47nQFDcBM6

[eliotwrobson]

For sure! I'll be sure to email this person as well, but this is @jeremyzhangsq

[eliotwrobson]

Shiqi has agreed to review and filled out the form!

[eliotwrobson]

@Batalex just wanted to check back in and see if there was anything we could do to help find a suitable editor for this. We're not in a huge rush or anything, but we want to submit this package to a conference before too long.

[Batalex]

Hello @eliotwrobson,
Unfortunately, I do not have an editor at the moment. There are two reasons for that: first, we are so successful our current editors have their hands full currently (let me brag a little). Second, the domain is more niche than others, so we (or more specifically I) cannot rely on personal connections or previous involvements to find someone with a relevant expertise. What would be your target conference? I'll see what I can do to help accelerate the process.

[eliotwrobson]

@Batalex Thank you for your detailed response. We don't quite have a target conference in mind, but we're starting more work on a longer version of what will be our paper for this. I mainly asked because we may be able to help search for an editor as well, depending on what the preferred qualifications are. For example, Shiqi has published papers related to this, and might be able to serve, depending on how heavy the workload is, and how difficult it would be to find two other reviewers.

Regarding this general area, anyone who has worked on projects related to influence maximization or even just general graph theory might know enough to get the ball rolling.

[sneakers-the-rat]

I can edit this, although I just was the editor for the automata package and maybe the authors want a break from me ;)

[eliotwrobson]

@sneakers-the-rat we would greatly appreciate you serving as editor 🙂

[sneakers-the-rat]

Happy to do it, i'll be able to get started searching for reviewers tmrw :). (i'll let the EiC do the formal assignment)

[cmarmo]

i'll let the EiC do the formal assignment

Thanks a lot @sneakers-the-rat and thanks to @Batalex who did the hard work as EIC here!
Happy review to all!

[eliotwrobson]

Awesome! @sneakers-the-rat just to fill you in, we've already identified a reviewer (@/jeremyzhangsq) who has papers published in this area. So the other reviewer doesn't necessarily need to be a subject area expert, and I think it would be appropriate to have someone with more knowledge of Cython packaging / best practices, since that was the part I was most unfamiliar with when writing this package.