Bursting the Filter Bubble

Jah-Wren Ryel writes with news that a few CS folks are working on a way to present opposing viewpoints without angering the reader. From the article: "Computer scientists have discovered a way to number-crunch an individual's own preferences to recommend content from others with opposing views. The goal? To burst the 'filter bubble' that surrounds us with people we like and content that we agree with. A recent example of the filter bubble at work: Two people who googled the term 'BP.' One received links to investment news about BP while the other received links to the Deepwater Horizon oil spill, presumably as a result of some recommendation algorithm." From the paper's abstract: "We found that recommending topically relevant content from authors with opposite views in a baseline interface had a negative emotional effect. We saw that our organic visualization design reverts that effect. We also observed significant individual differences linked to evaluation of recommendations. Our results suggest that organic visualization may revert the negative effects of providing potentially sensitive content."

its more than just political sensitivity

[Anonymous Coward]

i'm a generalist, i work in a few fields, including EE and CS - my colleague is pure CS

we're trying to have a conversation about a topic (distributed clocks) and based on our histories
we get entirely different search results, completely non-overlapping. his are general distributed
systems results and mine are narrowly turned to sensor networks

i had to ask him to make me a bibliography because I got sent into an entirely different
alleyway of the literature

thanks google

Interesting and useful for Slashdot

[mattr]

I only skimmed the paper briefly but it is interesting in that:
- User clicks a wordcloud keyword/hashtag that draws lines from it to multiple florets (individual nacelle-like microflowers in a sunflower head), each of which represents a tweet in recent portion of a feed.
- Repudiates the idea of filtering to meet viewer expectations so everyone can see the same content.
- A cuteness factor (or what they say is "organic" being like a flower) apparently reduces gut reaction to tweets you do not agree with
- Viewer is able to actively pick tweets to read. Presumably as the sunflower head image is mathematically generated and each floret's color could be tweaked to match a positive/negative sentiment score, allowing the user to pick only items that agree/disagree with them but to do so consciously.

This last point would seem to be ideal and I'd like to see slashdot include something more than the slider ("read only above this score"), particularly for a topic that has over say 500 or 800 replies. How about a data visualization that shows all the posts/threads for an article and lets the user select based on where in this chart a post is? At the very list, something 2-dimensional not 1-dimensional.

Re: "Organic visualization"

[Animats]

The "organic visualization" thing and its jargon are described in this thesis [benfry.com] done at the MIT Media Lab. This is what happens when postmodernists try to improve on Tufte. [edwardtufte.com] Some of it is pretentious bullshit. But there may be the genesis of some new phone apps in there.

Here's a good, but unrelated, example of "organic visualization": BitListen [bitlisten.com] This is a little HTML5/JavaScript page which depicts transactions on the Bitcoin block chain. An older example is Muckety [muckety.com]. This can be done well, but most attempts in this direction are duds.

Re:its more than just political sensitivity

[Kell Bengal]

The problem here is one of correlation vs causation. Someone is not always right simply because they are the 'expert'; likewise, someone is not always wrong simply because they are a layperson. However, when it comes to knowing what you're talking about, there is a strong dependence on experience and familiarity with the subject matter. The vast majority of the time we might expect that an expert who devotes all of their efforts to studying a problem will have some advantage over those who engage with a topic briefly. That is why we value expertise in the first place. It does sometimes happen that experts get it wrong while laypeople get it right, but it's pretty unusual.