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Is “Discoverability” Even A Problem?

Via booqlab
booqlab's curator insight, February 13, 2013 5:23 AM

This year, my favorite thing that happened throughout the entire day was, during a session on talking about “what readers want” proposed by Jeff O’Neal and Rebecca Schinsky of BookRiot, Laura Hazard Owen said after a pretty awesome leadup, “What if discoverability turns out to not even be an issue?”

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The Discoverability Problem: How To Get Out of the Filter Bubble Recommendation Systems?

The Discoverability Problem: How To Get Out of the Filter Bubble Recommendation Systems? | Industries creatives Industries |

Robin Good: Brett Sandusky attacks the "discovery" topic with simple, straight logic, analyzing what all the new startups and the new tech fanatics seem to systematically look over.

How can you help me discover new stuff, if you are intentionally limiting your exploratory gathering to algorithms and to, however varied, network of contacts?

She writes: "The discoverability problem in books is a challenge. It’s about connecting users to new and interesting titles, that they wouldn’t normally have seen. This last part bears repeating: …that they wouldn’t normally have seen.

Ultimately, the problem with all these discoverability sites is this: their algorithms (if they are even using an algorithm) are based on aggregate data in a one size fits all model.

The more people who read something, the more often it shows up in your recommendations. But, that’s not discoverability. That’s the NYT bestseller list. That’s Nielsen Bookscan telling you the top sales of the week.

Just because most of my friends are reading bestsellers (because, duh, whose aren’t? In fact, that seems to just reinforce the concept of the term “bestseller”) does that mean I should only be shown these titles?

Obviously, the answer is no. But, how do we get there?"

The answer is that we need a) more expert and qualified human intervention to unearth and pick new stuff, and b) behavioral data coupled with data collected on customer preference to allows us to connect those selected materials to the users in the system.

Rightful. Timely. 8/10

Find out:

(Image credit: Josephine Wall - Discovery)

Via Robin Good
Robin Good's comment, October 14, 2012 3:56 AM
Too bad that it is only in Russian, as I can't make much sense of whether there is real value in there or not. Or is it there a western language edition?
RPattinson-Daily's comment, October 14, 2012 8:20 AM
Robin Good, thank You for attention to my comment. Unfortunately, due to crisis of 2008 plans of creation its western language edition were terminated. However, concept, technologies, business model of such recommendation service for creative goods (books, movies, music) were described in book “The Economics of Symbolic Exchange” by Alexander Dolgin (2006) ( I was content curator, market researcher and editor of this book.
It can be read by parts/chapters depending on interest (see its Contents in Amazon). For example, chapter 1.3 about consumer navigation in creative industry such as online music market, ch.2.7 – survey of recommender systems. The music industry was first where recommendation systems based on collaborative filtering were implemented (for example Last.Fm, and many others). How well they are working you may check out for music – Last.Fm (, for movies – Netflix (
Robin Good's comment, October 14, 2012 9:12 AM
Thank you for clarifying this and having provided these useful references.