Consumer Facing Analytics for User Generated Media

Aggregating and analysing user generated media (blogs, boards, usenet, etc.) posts on products is what Intelliseek, BuzzMetrics, etc. do for a living. This level of analysis is not currently available in consumer facing products other than search (blog search, board search, usenet search) and some specialised search applications (trend search and the simple sentiment search of OpinMind). The content universes for enterprise products in this space include generally blogs, message boards and usenet and can extend to review sites and other genres.

On the other hand, there are social content hosting sites, such as riffs.com and amazon, which support research on products via aggregating content only found on their site - what we might call captured content search. These are useful to a degree. However in order to get a fuller picture - one might say a more accurate picture - of what people think about products, or any topic for that matter, a solution is required which is capable of spanning multiple content types.

When considering user generated media, we are forced to consider the boundary between this type of content and professional content. A boundary which has blurred considerably in the last year and will continue to do so. In other words, there is a problem in deciding when to include opinion from the professional end of the spectrum and how. For example, how does one weigh a movie review from a blog, a movie review from rotten tomatoes, and one from, say, Mr. Ebert? An additional issue when providing consumer facing interfaces for this type of data is capturing the product being researched and finding those posts that refer to it. The captured content, especially in sites like amazon, may well have the advantage of a complete taxonomy of products which can be searched against rather than the content of the reviews. In other cases, the user requires assistance in accurately retrieving results for all variations of expressions used to refer to the product.

In this context, it is interesting to note two developments. First is Google's review search, which Kevin pointed to. This appears to aggregate reviews from a number of sources (and types of sources) for movies. It also provides access (in a faceted search type of interface) to positive, negative and neutral reviews (based on segmentation via numeric review scores). Not only that, but it provides common phrases mined from the reviews. This is pretty cool, and brings features found in standard enterprise offerings to the consumer. Note that BlogPulse has had consumer facing features based on similar features for over a year - for example blog bites, which both extract common terms and find snippets which contain terms with significant relationships.

I'll post a deeper dive on Google's review stuff later.

The second new consumer facing user generated media interface is reported by Smart Mobs, and TechCrunch and appears to be a service which will allow users to use their phones to input bar code data on a product and access user generated commentary drawn from blogs.

Is 2006 going to be the year of consumer facing analytical tools over the user generated media space? And how will the enterprise players in this space respond?

Comments

[Kevin Burton]

This is anecdotal at best but I'm finding that online review systems like IMDB seem to result in a moderate rating. Take a movie which is popular and the mean seems to be around 7.5... Of course I'm willing to get the median is somewhere around 9.5...

Kevin

[Matthew Hurst]

There are other biases - for example, in free text, female authors tend to use slightly more positive language than male wrt overall volume and so if this carries through to numeric scoring then filtering by number will bias the reviews to female reviewers.