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Friday, February 3, 2023

Boxxet Offers "Best Of" Collections On Popular Topics

Boxxet is a new service which combines aspects of computer automation with community and social commentary and ranking systems to create “box sets” of web based content for specific topics.

It’s an interesting idea—sort of a multimedia directory of links to web, news and blog content, photos, forums, online bookmarks and “stuff,” products available for online purchase that relate to a particular subject. The idea is to filter the mass of information available online, presenting only the best or freshest content. While the resulting “box sets” are generally on topic, ironically, I found myself a bit overwhelmed more often than not.


Boxxet launched just yesterday, so it’s still very much a work in progress. Currently, Boxxet is heavy on sports and entertainment, with a smattering of collections on other subjects like cars, fashion and technology. Over time the quantity and variety of boxxets should grow. But don’t bother looking for collections on anything other than mainstream, popular topics at this point.

I checked out a few boxxets on topics I’m familiar with, to see how well they represented what I felt are the best sources of information and other content.

Major league sports are well represented in boxxets, so I looked at the Colorado Avalanche hockey team boxxet. The “best” page told me the top news sources, blogs and bookmarks, and also displayed headlines from the past week or so. While Boxxet does try to aggregate stories by subject, similar to the way Google News operates, it also displayed a lot of different headlines covering the same story. While many of the sources seemed good, my favorite source of Avalanche news, the Denver Post, wasn’t represented in headlines (it was ranked #49 by Boxxet users and included as a “bookmark,” however).

Also, the sheer number of links to stories from sources I have absolutely no interest in reading, such as OregonLive.com, the Houston Chronicle and “Ang’s Weird Ideas” (what do they know about my home team?) led to a definite feeling of information overload—exactly the opposite of what Boxxet is trying to accomplish by filtering sources of information.

The photo selection was awful—pictures of mountains, the Chevy Avalanche truck, several others I have no clue about, and a handful of pictures of actual Avalanche hockey players. Boxxet has three buttons to let you select “good,” “better,” or “best” photos and to be fair, clicking the “better” button increased the number of hockey pictures (though clicking “best” got rid of all pictures but one showing a two-week old photo of Avalanche player Andrew Brunette).

The merchandise selection in the “stuff” category seemed OK, though it was all offered by Amazon Apparel, from what I could tell.

I checked out other boxxets for science fiction author Neal Stephenson, the band Radiohead, and the Apple iPod, and in each case found some really great content that I was unfamiliar with—but also some really dubious stuff that was either off-topic or junk.

In part, this is because the Boxxet user community is still comparatively small, and the filtering based on votes and tagging doesn’t have enough of a sample to make good judgments about content. This is one of the most significant challenges faced by all systems that attempt to enhance algorithmic suggestions with human judgments.

Despite the drawbacks, I like the idea behind Boxxet and am willing to give it a chance to grow and evolve, and hopefully to improve as more and more people contribute their knowledge and opinions to the service. I’ll check back with it in a few months to see how it has grown.

You can find more info about Boxxet and its creators here.


Opinions expressed in this article are those of the guest author and not necessarily Search Engine Land. Staff authors are listed here.


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