Fudge Sunday - Twitter, Matter, and Data-Driven Journalism
This week is a departure from diving into cloud topics. I’ll spend a few paragraphs describing how I’m using Twitter, Matter, and seeking more Data-Driven Journalism.
Twitter’s call to action is simple.
These days, my tweets are less often and cleaned regularly via Tweepy. Also, I noticed what was happening trended away from what I wanted in my Home feed even if sorted by time.
As an experiment, I decided to be more manual and purposeful with what I’m reading on Twitter. The goal was to find an alternative to the Home feed that is algorithmic curation and, well, lots of advertising.
Specifically, I’ve stopped Following anyone on Twitter. Instead, I simply curating my own Lists based on a great insight from Aaron Delp.
Went back to using Twitter lists vs. the timeline algorithm. It is amazing how many tweets from people I follow that are just NEVER seen using the standard timeline. Not going back, Twitter is barely usable in current state
What’s the impact? For starters, Home view in Twitter is quite spartan.🤣
aka "Not followed by anyone you’re following" becomes the rule not the exception
Again, my new approach is to use Lists instead of Follow functionality. By using Lists functionality, I see what I want to see without advertising.
I have more Lists but they are "private" to my interface view.
So far, the only perceived downside is that I am compelled to see Retweets that could otherwise be filtered completely through Follow functionality. However, compared to the Home feed before this is worth it.
p.s. I used this gist to help with getting some of the Retweets pruned from standard Follow views on Home.
What's the Matter?
I like reading newsletters. So, when I reached +50 newsletters it also coincided with regularly declaring inbox bankruptcy.
There had to be a better way.
[ Matter has entered the chat… ]
It is not hyperbole to say Matter brings new joy to daily newsletter reading and joy to listening to what you might not have time to read on a screen.
Matter - Read-it-later, reinvented
Quote from Product Hunt:
“Matter is a powerful, elegant read-it-later app that pulls in your newsletters, lets you listen to your articles in a natural voice, and much more.”
Curiously, if you are reading Revue based newsletters (like this one!) or other newsletters with similarly heavy HTML nested tables layouts, you might see some rendering issues on Matter. Your mileage may vary.
That said, the Revue team is aware and has been very responsive to the concerns I’ve shared.
Speaking of reading…
If a picture is worth a thousand words, animated visualization is probably worth ten thousand words and an interactive visualization will likely be worth one hundred thousand words in our ever brighter future ***.
Yes. There is the “DIKW” hierarchy or progression or journey of Data, Information, Knowledge, and Wisdom. Getting to the end of such a journey is often fraught with peril and with seemingly unlimited commercial interruptions online.
So, just as I’ve tried to limit my Twitter fast news hot take outrage intake and the geometric expansion of newsletters that are slower to publish, I’m also thinking about the data that might be synthesized as information I want to bring into focus.
In no particular order, I’ve been spending time clicking around these links more lately to see where the rabbit hole leads me in seeking knowledge:
The Associated Press team lets you follow their code on GitHub.
NYT Newsroom Developers · GitHub
The New York Times Newsroom Developers team lets you follow their code on GitHub.
Data journalism videos, long reads, and discussions.
Northeastern’s School of Journalism articles.
A visual timeline of the world’s most media-inflamed fears aka Mountains Out of Molehills.
*** Ever brighter future? Indeed. Perhaps? Glass half empty? Glass half full? This is a fun quiz to test your biases and possible media influenced perceptions.
As always, tune in again next week as I continue to attempt sharing some (cultured) pearls of wisdom.
If this is your first time reading or as a reminder, I work at Faction.
What’s Faction you ask? Faction helps companies on a multicloud journey as their essential data partner for maximizing cloud data services access to hyperscale public cloud service provider innovations.
We’re hiring at Faction!🎉🤓☁️🚀
To see our current openings click here. ⬅️🤓☁️🚀
See a fit for you or someone in your network? ✅🤓☁️🚀
Please don’t hesitate to reach out to me.☎️🤓☁️🚀
Want to learn more? Here are some recent Faction related articles:
Storage & Data Protection: A Multi-Cloud Strategy by Alyson Langon
Intelligent CIO’s Myths of Multi-Cloud by Matt Wallace
Dataversity’s The Hidden Costs of Cyber Attacks by Mike Phelan
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