Another very interesting article, thank you Erman. It sparked a question for me. You suggest exploring out-group opinions (which I totally see the value of and wholeheartedly endorse): do you have any practical advice on how to do that on social media where algorithms seem to reinforce the in-group bias?
This is a great question, Valerie. It's not always easy to do on social media, because as you say, algorithms are designed to show you what you love to see. However, with a platform like Twitter, you can actively choose to follow specific people who stand on different sides of a debate to you. Once you actively follow someone, you'll typically see their content.
So if you lean left/right on politics for example, you can actively search for the most respected and reasonable people you can find on the opposing side and follow them. Similarly, if you're trying to learn more about a controversial scientific question (e.g. "did coronavirus originate in a lab?"), you can look for qualified experts leaning toward yes and no answers and follow both.
Unfortunately, you can't rely on algorithms to show you the best versions of arguments on all sides of a debate. In fact, you'll often see the weakest examples of opposition arguments because they're easier to laugh or get angry at (those are highly monetized emotions on social media!). It takes some careful effort and research to find reasonable people on the side of a debate that's typically hidden from you. But I think it's well worth the effort and gives you a better-rounded view of what's going on out there!
Thanks so much for commenting. Hope that's somewhat helpful.
Super helpful, Erman. The approach you suggest makes a lot of sense. The only challenge I have is: the time it takes!
Unrelated, but reacting to words you used: do you know where I could potentially find out more about how emotions are monetised on social media? You seem to know so much... 😬
They link to some relevant science papers in that piece if you're interested. And here's a 2021 paper showing that angry reactions directed at out-groups predict strong social media engagement (very relevant to my newsletter here 😊 ): https://www.pnas.org/content/pnas/118/26/e2024292118.full.pdf
Another very interesting article, thank you Erman. It sparked a question for me. You suggest exploring out-group opinions (which I totally see the value of and wholeheartedly endorse): do you have any practical advice on how to do that on social media where algorithms seem to reinforce the in-group bias?
This is a great question, Valerie. It's not always easy to do on social media, because as you say, algorithms are designed to show you what you love to see. However, with a platform like Twitter, you can actively choose to follow specific people who stand on different sides of a debate to you. Once you actively follow someone, you'll typically see their content.
So if you lean left/right on politics for example, you can actively search for the most respected and reasonable people you can find on the opposing side and follow them. Similarly, if you're trying to learn more about a controversial scientific question (e.g. "did coronavirus originate in a lab?"), you can look for qualified experts leaning toward yes and no answers and follow both.
Unfortunately, you can't rely on algorithms to show you the best versions of arguments on all sides of a debate. In fact, you'll often see the weakest examples of opposition arguments because they're easier to laugh or get angry at (those are highly monetized emotions on social media!). It takes some careful effort and research to find reasonable people on the side of a debate that's typically hidden from you. But I think it's well worth the effort and gives you a better-rounded view of what's going on out there!
Thanks so much for commenting. Hope that's somewhat helpful.
Super helpful, Erman. The approach you suggest makes a lot of sense. The only challenge I have is: the time it takes!
Unrelated, but reacting to words you used: do you know where I could potentially find out more about how emotions are monetised on social media? You seem to know so much... 😬
There's lots of content out there on how emotions interact with social media activity, but here's one article I like on moral outrage: https://nautil.us/how-social-media-exploits-our-moral-emotions-7333/
They link to some relevant science papers in that piece if you're interested. And here's a 2021 paper showing that angry reactions directed at out-groups predict strong social media engagement (very relevant to my newsletter here 😊 ): https://www.pnas.org/content/pnas/118/26/e2024292118.full.pdf
Thank you so much for taking the time, Erman! I really appreciate it.