Reading outside your area of interest
A reasonable amount of the information that I consume comes either via scanning twitter or from my prismatic feed but I noticed that I’m quite biased to reading things in similar subject areas.
I tend to end up reading about data mining/science, functional programming and startups and while the articles are mostly interesting it does eventually start to feel like you’re in an echo chamber.</li>
I have a subscription to the ACM mainly because I enjoy reading the 'Communications of the ACM' magazine which gets sent out every month and until recently I only read articles which I thought would be interesting.
This unfortunately meant that I was adding to the problem I mentioned earlier whereby everything I read is about similar topics.
I decided to try and change that by reading the magazine from cover to cover and although I haven’t finished yet it’s been an interesting experience and I’ve read about things that I wouldn’t have thought to read about including:
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Do more computer science papers get rejected than those in other subjects?
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How do we allow people to vote in areas where there’s been a natural disaster?
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Why are there currently so many post-docs in computer science?
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How should we go about analysing performance problems?
This seems to be a reasonably good way of diversifying what I read/learn because an editor has decided what I should read rather than me choosing or an algorithm choosing based on what I’ve previously read.
Having said that, I’d be intrigued to know what approaches/strategies others have for getting knowledge of a broader range of topics.
About the author
I'm currently working on short form content at ClickHouse. I publish short 5 minute videos showing how to solve data problems on YouTube @LearnDataWithMark. I previously worked on graph analytics at Neo4j, where I also co-authored the O'Reilly Graph Algorithms Book with Amy Hodler.