Is Blog Search Different?

Alerted by Jeff and Iadh, I recently read What Should Blog Search Look Like?, a position paper by Marti Hearst, Matt Hurst, and Sue Dumais. For those readers unfamiliar with this triumvirate, I suggest you take some time to read their work, as they are heavyweights in some of the areas most often covered by this blog.

The position paper suggests focusing on 3 three kinds of search tasks:

1. Find out what are people thinking or feeling about X over time.
2. Find good blogs/authors to read.
3. Find useful information that was published in blogs sometime in the past.

The authors generally recommend the use of faceted navigation interfaces--something I'd hope would be uncontroversial by now for search in general.

But I'm more struck by their criticism that existing blog search engines fail to leverage the special properties of blog data, and that their discussion, based on work by Mishne and de Rijke, that blog search queries differ substantially from web search queries. I don't doubt the data they've collected, but I'm curious if their results account for the rapid proliferation and mainstreaming of blogs. The lines between blogs, news articles, and informational web pages seem increasingly blurred.

So I'd like to turn the question around: what should blog search look like that is not applicable to search in general?

Information Retrieval Systems, 1896 - 1966

My colleague and Endeca co-founder Pete Bell just pointed me to a great post by Kevin Kelly about what may be the earliest implementation of a faceted navigation system. Like every good Endecan, I'm familiar with Ranganathan's struggle to sell the library world on colon classification. But it is still striking to see this struggle played out through technology artifacts from a pre-Internet world.

A Game to Evaluate Browsing Interfaces?

I've mused a fair amount about to apply the concept of the Phetch human computation game to evaluate browsing-based information retrieval interfaces. I'd love to be able to better evaluate faceted navigation and clustering approaches, relative to conventional search as well as relative to one another.

Here is the sort of co-operative game I have in mind. It uses shopping as a scenario, and has two roles: the Shopper and the Shopping Assistant.

As a Shopper, you are presented with an shopping list and a browsing interface (i.e., you can click on links but you cannot type free text into a search box). Your goal is to find as many of the items on your shopping list as possible within a fixed time limit. In a variation of this game, not all of the items on the list are findable.

As a Shopping Assistant, you know the complete inventory, but not what the Shopper is looking for. Your goal is to help the Shopper find as many of the items on his or her shopping list as possible within a fixed time limit. On each round of interaction, you present the Shopper with information and links within the constraints of a fixed-size page. The links may include options to select items (the Shopper's ultimate goal), as well as options that show more items or modify the query.

Either role could be played by a human or a machine, and, like Phetch, the game could be made competitive by having multiple players in the same role. I'd think the interesting way to implement such a game would be with human Shoppers and algorithmic Shopping Assistants.

Is anyone aware of research along these lines? I'm hardly wed to the shopping list metaphor--it could be some other task that seems suitable for browsing-oriented interfaces.

Idea Navigation

Last summer, my colleague Vladimir Zelevinsky worked with two interns, Robin Stewart (MIT) and Greg Scott (Tufts), on a novel approach to information exploration. They call it "idea navigation": the basic idea is to extract subject-verb-object triples from unstructured text, group them into hierarchies, and then expose them in a faceted search and browsing interface. I like to think of it as an exploratory search take on question answering.

We found out later that Powerset developed similar functionality that they called "Powermouse" in their private beta and now call "Factz". While the idea navigation prototype is on a smaller scale (about 100k news articles from October 2000), it does some cool things that I haven't seen on Powerset, like leveraging verb hypernyms from WordNet.

Click on the frame below to see the presentation they delivered at CHI '08.



Idea Navigation: Structured Browsing for Unstructured Text

Clarification vs. Refinement

The other day, in between braving the Hulk and Spiderman rides at Endeca Discover '08, I was chatting with Peter Morville about one of my favorite pet peeves in faceted search implementations: the confounding of clarification and refinement. To my delight, he posted about it at findability.org today.

What is the difference? I think it's easiest to understand by thinking of a free-text search query as causing you to be dropped at some arbitrary point on a map. Our planet is sparsely populated, as pictured below, so most of the area of the map is off-road. Hence, if you're dropped somewhere at random, you're really in the middle of nowhere. Before you start trying to find nearby towns and attractions, your first task is to find a road.

How does this metaphor relate to clarification vs. refinement? Clarification is the process of finding the road, while refinement leverages the network of relationships in your content (i.e., the network of roads connecting towns and cities) to enable navigation and exploration.

"Did you mean..." is the prototypical example of clarification, while faceted navigation is the prototypical example of refinement. But it is important not to confuse the concrete user interfaces with their intentions. The key point, on which I'm glad to see Peter agrees, is that clarification, when needed, is a prerequisite for refinement, since it gets the user and the system on the same page. Refinement then allows the user to fully exploit the relationships in the data.

Social Navigation

There has bit a lot of recent buzz about social navigation, including some debate about what the phrase means. I dug into the archives and found a paper from the CHI '94 Conference on Human Factors in Computing Systems entitled "Running Out of Space: Models of Information Navigation". In it, Paul Dourish and Matthew Chalmers distinguish between semantic navigation and social navigation:

[semantic navigation offers] the ability to explore and choose perspectives of view based on knowledge of the semantically-structured information.
...
In social navigation, movement from one item to another is provoked as an artifact of the activity of another or a group of others.

Back in 1994, the Web was only starting to reach a broad audience. The authors cite two examples of social navigation: personal home pages, where people listed sites they found interesting, and collaborative filtering (specifically, the Information Tapestry project at Xerox PARC).

Today, a decade and a half later, the web has scaled by several orders of magnitude, search engines have largely obviated the listing of interesting sites on personal home pages, and collaborative filtering, while still going strong as a social influence on user experience, hardly feels like navigation. It does seem that the term "social navigation" deserves an update.

Following Dourish and Chalmers, let us define social navigation as the ability to explore and choose perspectives of view based on social information. Importantly, social navigation is user-controlled navigation just like semantic navigation--only that the user is navigation by changing the social lens on the information rather than specifying semantic constraints.

One example of social navigation is the ratings information at the Internet Movie Database (IMDB). For example, we can see from the ratings for Live Free or Die Hard that the movie appealed most to males under 18.

Fandango (an Endeca customer) takes this concept a step further, offering users faceted navigation of the space of movie reviews, where facets include age, gender, whether or not the reviewer has children, and whether the reviewer lives near the user.

More sophisticated interfaces will intermingle semantic and social navigation. Here is a screen shot from a prototype some of my colleagues put together and demonstrated at HCIR '07:

Social navigation, defined as above, offers users more than just the ability to be influenced by other people. It offers users transparency and control over the social lens. It allows us to think outside the black box.