With solutions like Paper.li and Browse My Stuff grabbing attention, and with people like Robin Good doing a series on Real-Time News Curation, and Ross Dawson tells us has curation has hit the tipping point, it seems like the concepts of curation, aggregation, filtering are suddenly a central conversation. Of course, this has long been a conversation as Robin, Ross or I could tell you. However, what has really changed here is first the explosion of content sources. As Robin put it:
“You cannot follow and keep yourself updated in an effective way by simply subscribing to as many sources as possible.”
I would also say that what has really changed is the sophistication of automated filtering to deal with extracting value from the noise. I had an interesting exchange with Robin around the question of what constitutes filtering and how that differs from curation. I’ll get to that in a bit. Let’ me first provide some background on filtering.
Approaches to Automated Filtering
In Different Approaches To News Filtering, Mahendra Palsule who is an editor at TechMeme, identifies the following ways to automatically filter content. Adding in a few from Louis Gray’s The Five Stages of Filtering, Relevance and Curation, I believe there are roughly the following types of automated filtering mechanisms:
- Text Filtering – exclude-include specific keywords, terms and phrases
- Semantic Filtering – exclude or include based on semantic analysis of content
- Explicit Crowdsourced Filtering – using voting mechanisms to identify what people prefer, e.g., Digg.
- Social Filtering – using social signals for implicit crowdsourced filtering. This can take several forms:
- Explicit Personalization – Based on what you have told us you like or don’t like, or where you are located, the system will filter the results, e.g., Netflix’s, MeeHive.
- Implicit Personalization – Based on what you have done in the system, it automatically filters. This is being done by Google search as well as Amazon.com and my6sense.
Of course, it’s likely the case that any effective automated filtering mechanism will combine several of these to derive even better results. And, of course, “better” is often hard to define.
Aggregation, Automated Filtering and Curation
In Real-Time News Curation – The Complete Guide Part 2: Aggregation Is Not Curation, Robin good talks in detail to the following:
- Aggregation is not curation
- Filtering is not curation
- Aggregation is Automated, Curation is Manual
- Automated Aggregation without Curation, is mostly spam
- The Solution is in the MIX – Human Curation + Machine Aggregation
Robin and I agree on the definition of aggregation as the bringing together of content from various sources, filtering is finding the good stuff (removing noise and ranking the rest), and curation is about organizing, maintaining and adding value to a body of information for current and future use.
Where we disagree is whether there are forms of automated curation. Robin believes that for something to be curated there must be a human doing manual curation. Robin believes that this must be manual and I believe he also sees this as a single individual or small group of editors.
Where I think he runs into problems is when there are many people involved, possibly a crowd, or even everyone. Maybe even there are different levels of these people. The crowd does curation using explicit crowdsourced filtering or via social signals. This results in filtering and ranking. Then maybe a smaller group of individuals does additional filtering, ranking. And maybe they do this explicitly or implicitly.
In any case, it’s very hard to separate social filtering from curation. For me, I will continue to refer to curation via social signals as curation. I don’t disagree that additional curation from direct involvement of active, human curators will produce additional information that can be used. But I also see a bit of John Henry vs. the Steam Drill here. See an example in Filtering and Curation of Specific Topics.
I’m also a bit worried that many traditional publishers will read Robin’s post and believe that they should continue to focus on human powered curation to their detriment. As Steve Rosenbuam asks, Can Curation Save Media? To me, it only can save publishers if they rapidly move to take advantage of automated filtering as opposed to human-powered curation. Otherwise, they will be like John Henry and fight incredibly hard only to die.
Still all of this argument likely leaves Robin and I in the same place. I thought that David Koretz in You’re Not That Interesting captured it pretty well:
Successful media will become aggregators and editors of content, rather than creators. The smart money will build a technology to gather, sort, and filter stories from every corner of the world, and couple it with smart and thoughtful humans to do the editing.
He’s right on about who will likely win at the end. Just be careful that you don’t make your editors do too much manual curation and die fighting the machine.