How to keep up with academic literature
By: Krishna Rao
Tags: Academia, Reading, Science, Education, Towards Data Science

How to keep up with academic literature

Learn to do literature review efficiently and consistently

Keeping up with academic literature is like trying to drink water from a fire hydrant — it seems impossible to keep up! (credits to Alex Konings). Artwork from dlpng.com, freepik.com.

Academic publishing is exploding. More than 2.5 million papers are published every year and the fact that the pace of publishing is climbing 8% every year isn’t helping. With so much to read out there, it is easy to feel like we’re barely keeping our heads above the water.

Unfortunately, keeping up with literature is one of those things — like walking — that isn’t really taught to us. We are expected to learn it by ourselves. However, over the past few years, I have realized that even though we have our own styles of finding and reading papers, there are some common good practices held by many, but not known to all. This became apparent to me only after I sat in a classroom and learnt how to keep up with literature (lecture by Andrew Ng).

In this article, I will combine those lessons with other valuable insights from my colleagues, professors, and my own experience. By the end of the article we would have learnt:

How to find papers that are relevant to us? How to read those papers efficiently using the three-pass approach? Why consistent reading beats bursts of activity?

What to read? A curated set of articles.

Even before we learn how to read efficiently, one way to keep up with academic literature is to narrow our scope and choose what we read carefully. Unless you are a polymath like Da Vinci, your field of interest is likely narrow enough to be defined using 6–10 keywords. As I am an Earth Scientist, I use keywords like “wildfire”, “forest mortality”, etc.

You may use as many key words as you like to define your scope, but try to keep each keyword specific. For example, “deep learning” is a terrible keyword because it is not specific enough. It will lead to thousands of irrelevant papers and to find what is relevant to you among them is akin to finding a needle in a haystack. On the other hand, “Image segmentation” is a good keyword as it is specific. Finally, don’t be shy to update your keywords with time to reflect your changing interests.

Using specific keywords like “image segmentation” is preferred to broad keywords like “deep learning” to decrease the clutter and keeping your reading list manageable. Data source: Web of Science. Image by Author.

Once you have defined your keywords, use any of the following resources to gather literature relevant to you-

Online search on Google Scholar (free), Scopus (paid), or Web of Science (paid). This option is only effective for one-time searches. You cannot rely on this solely for keeping yourself up to date with literature (explained later). Conference proceedings Twitter- Use your keywords to search for the right people and follow them. Friends and colleagues- Leverage your network to find the right papers. You can return the favor to them if you find papers from their area. Google Scholar alerts- Set up alerts with your keywords or “follow” the professors whose work you are interested in. Table of contents- Setup alerts to receive the table of contents of the journals where articles from your area are frequently published. JournalTOCs is a great service as it combines and sends alerts for most journals. People have varying views regarding the importance of looking through the table of contents. However, I have found it useful to get over the feeling of having blinders on — it gives a peek into the developments in the broader scientific world.

Once we have compiled a curated list of papers using our keywords, we can read them using the three-pass approach.

How to read? The three-pass approach visualized.

While reading the papers, we want to make sure that we read all the important and relevant papers in detail while skimming through the rest. Of course, there is no way of knowing what is important beforehand. Thus, reading each paper from start to end is not a valuable use of our time since each paper’s relevance differ — some may be important for their background, some may help motivate our particular project, some may have analyses that we would like to replicate, and some might have results that go against our initial hypotheses (and thus very important to read thoroughly).

Do not waste your time sequentially reading each paper from beginning to end. Image by Author.

Instead of reading each paper sequentially, I find that the three-pass approach (paper by S. Keshav) of reading papers not only helps me identify the important papers for my project, but also lets me focus on the relevant sections within each paper. This way, I can do multiple passes per paper, with each pass getting into greater depths

Round 1: The highlights.

Round 1: Title, abstract, and figures+captions. Artwork from freepik.com.

Round 1 consists of reading the title, abstract, and figures+captions. This round is meant to just grab the highlights of a paper without going through its details. The title and abstract will help us grab the main conclusion of the paper. The figures provide the results at a glance.

Keep in mind that we still haven’t learnt about the exact results, or the background motivating the paper, which is perfectly fine. At this stage, we are mostly interested in “what” of a paper without being concerned about “why” or “how”. Since Round 1 is fairly short, I cover every paper I collect from the previous section in this round.

Some food for thought to keep in mind during Round 1:

What did the authors try to accomplish? How can the figures be made better? (a useful skill to learn, regardless of the paper content)

At the end of round 1, we can filter out those papers that were clearly not linked to our topic of interest. We then proceed to round 2.

Round 2: The core.

Round 2: Introduction, results, conclusions, figures+captions, skim the rest. Artwork from freepik.com.

Round 2 consists of reading the introduction, results, conclusions, figures+captions, and skimming the rest. This is where we really start to understand the papers. The introduction will help us align with the need for the research, while the results and conclusions will help us understand the findings of the paper clearly. I find that this is the round in which I learn the most.

Some prompts to keep in mind during Round 2:

What ideas or data can you use yourself? What references do you want to follow?

Round 3: The details.

Round 3: Methods, Discussion, References, skim the rest. Artwork from freepik.com.

Round 3 consists of reading the methods, discussion, noting some references, and skimming the rest. This round is meant to get into the depth of the papers. By going through the methods in detail, we should be fairly confident of being able to replicate the approach ourselves. Since we dive deep into the papers in Round 3, this round is reserved only for those papers that are directly relevant to our topic of interest.

Since we have gone through multiple rounds by the end of this round, it is a good time to make a note of all the papers which were cited frequently among the initial set of papers. The added focus on the discussion section should in round 3 should also point us to other relevant papers with similar findings or where the results might be of high importance.

Some prompts to keep in mind during Round 3:

What are the key elements of the approach? What references do you want to follow?

What a three-pass might look like. Image by Author.

With the three-pass approach, I am able to read through ~25 papers a week without spending too much time on those that are not of much relevance to my current interest. It thus saves me a lot of time, without compromising on my need of keeping up with academic literature. However, it is successful only if it is performed frequently.

When to read? Everyday!

If you take away just one thing from this article, let it be this- When it comes to reading, consistency beats bursts of activity. While literature review is no doubt useful during the start of a new project, it is not an activity meant for only the start. Not reviewing literature consistently, leaves us prone to become outdated. This is even more true in budding fields like deep learning where papers from 4 years ago are considered old.

Aim to be consistent with your reading. Image by Author.

Not being consistent with reading is dangerous for 2 reasons-

Once the initial round of literature review is completed we are no more up to date with the latest developments in our field There is a greater chance of missing out on some important paper which we hadn’t covered initially

The latter consequence hit me in the face at a conference when someone asked me after my presentation, “Why did you assume X when paper Y showed that it does not hold true in cases like yours?” Generally speaking, there are several acceptable answers to such questions, but none of those start with “I have not read that paper, but …”. Since then, I have been reading at least 1 paper every night before going to sleep and it has greatly helped me keep up with the literature.

A paper a day keeps embarrassment at bay.

Conclusion

In this article, we learnt how to keep up with academic literature. While an online search is ok, it is vital to use tools such as scholar alerts or table of content alerts that feed us with papers frequently. With a curated set of papers, we can then follow the three-pass approach to efficiently read through them — first to grab the highlights, then to get into the core, and finally to understand the details of the papers. At the end of each round, feel free to drop the papers that are not relevant to your topic of interest. Lastly, through my own embarrassing experience, I hope you value the need for reading daily and do not set aside literature review as a one-time activity.