Really cool article, thank you for sharing! That's neat that it's already been in effect in some ways. Polis sounds interesting. I think it would be cool to see the differences in a person's...
Really cool article, thank you for sharing!
The core logic of bridging-based ranking has already been used on Facebook and X (formerly known as Twitter), albeit not in the main feed. It is also used in Polis, an online platform for collecting public input, used by several governments to inform policymaking on polarized topics.
That's neat that it's already been in effect in some ways. Polis sounds interesting.
I think it would be cool to see the differences in a person's social media feed between the engagement model and the bridge-building model.
I like that the article touched on the roles of mediators, facilitators and peacebuilders who work on bridging communication between opposing groups. I'm interested in learning more what techniques they use in their jobs.
I do think it would be beneficial to see more content that encourages finding similarities between people rather than driving people apart with their differences.
While I very much support a departure from engagement-driven metrics, I fear there is still a possibility for fostering echo-chambers and filter-bubbles by focusing just on similarities. Exposure...
I do think it would be beneficial to see more content that encourages finding similarities between people rather than driving people apart with their differences.
While I very much support a departure from engagement-driven metrics, I fear there is still a possibility for fostering echo-chambers and filter-bubbles by focusing just on similarities.
Exposure to differing viewpoints (especially minority viewpoints) can open worldviews and increase empathy. Taken to an extreme, though, it can also lead to the same rage-bait we see today, so there’s a delicate balance to be had.
I think social media was most “social” when it was a chronological feed of just your friends. Since the cat’s out of the bag of connecting local users to the global userbase, we need to address the fact that toxic users feel protected by a general level of anonymity or geographic distance (perfect ingredients for troll farms to operate).
The article links to a report which includes some slightly more nuanced examples of what a briding algorithm could encourage. One of the examples I especially liked was one where a user from one...
While I very much support a departure from engagement-driven metrics, I fear there is still a possibility for fostering echo-chambers and filter-bubbles by focusing just on similarities.
The article links to a report which includes some slightly more nuanced examples of what a briding algorithm could encourage. One of the examples I especially liked was one where a user from one “side” (party, viewpoint, etc.) writes a longer-form post, which is then widely shared by users of the other “side” who are likely to read to the end and leave comments on the post, to which Alice replies. What I like about the example is it shows how a bridging metric could select not just for points of agreement, but for civil and thoughtful dialogue on disagreements, potentially just by looking at the structure of engagement (although in a real-world application, I imagine sentiment analysis would also be involved).
Really cool article, thank you for sharing!
That's neat that it's already been in effect in some ways. Polis sounds interesting.
I think it would be cool to see the differences in a person's social media feed between the engagement model and the bridge-building model.
I like that the article touched on the roles of mediators, facilitators and peacebuilders who work on bridging communication between opposing groups. I'm interested in learning more what techniques they use in their jobs.
I do think it would be beneficial to see more content that encourages finding similarities between people rather than driving people apart with their differences.
While I very much support a departure from engagement-driven metrics, I fear there is still a possibility for fostering echo-chambers and filter-bubbles by focusing just on similarities.
Exposure to differing viewpoints (especially minority viewpoints) can open worldviews and increase empathy. Taken to an extreme, though, it can also lead to the same rage-bait we see today, so there’s a delicate balance to be had.
I think social media was most “social” when it was a chronological feed of just your friends. Since the cat’s out of the bag of connecting local users to the global userbase, we need to address the fact that toxic users feel protected by a general level of anonymity or geographic distance (perfect ingredients for troll farms to operate).
The article links to a report which includes some slightly more nuanced examples of what a briding algorithm could encourage. One of the examples I especially liked was one where a user from one “side” (party, viewpoint, etc.) writes a longer-form post, which is then widely shared by users of the other “side” who are likely to read to the end and leave comments on the post, to which Alice replies. What I like about the example is it shows how a bridging metric could select not just for points of agreement, but for civil and thoughtful dialogue on disagreements, potentially just by looking at the structure of engagement (although in a real-world application, I imagine sentiment analysis would also be involved).