Skip to Content
Uncategorized

A Startup Finds a Better Way to Mine Your Facebook Past

The Trove search engine feeds on everything you and your friends have shared.
October 12, 2012

It’s common to compare how many friends you have on Facebook with other people. But a more meaningful measure of your account’s worth is shown by Trove, a search engine that feeds on the entire history of your Facebook account to help you find useful bits of information. It tells you exactly how many items—status updates, photos, and more—you and your friends have uploaded and provides a search box that can trawl through every one of them. Google can’t do that, because it doesn’t make it possible for you to grant its search technology access to your Facebook account. Given the rivalry between Facebook and Google, it’s unlikely that will ever happen.

In my case, Trove can sift through 100,070 different items, a rich heap of content that is almost impossible to find via Facebook’s site. In reference to search, Mark Zuckerberg boasted last month that his company was well positioned to launch a search engine, saying “we’re basically doing one billion queries a day and we’re not even trying,” but Facebook’s current search engine is only good for finding people or apps (see “Facebook Eyes Search”).

Facebook users can browse through older photos and updates using the timeline-style profiles introduced last year. But it feels more like rifling through a filing cabinet by hand than using smart technology to retrieve things of interest.

Trove changes that. It’s designed to match the model of search introduced by Google, with a search box in the center of an almost white screen. And it only takes a few exploratory searches to understand that there’s more useful information in your Facebook account than you realize.

The social network encourages users to forget yesterday’s or last week’s content, and pushes us toward the new, even filtering out recent items it guesses we won’t care about. But while a news feed of old news isn’t much of a draw, old conversations and photos gain new relevance when you can summon them with keywords or phrases.

One example I stumbled on quickly was using Trove as a better way to browse photos, through exploratory searches such as “wedding” or “birthday.” Searching for photos matching “Halloween” returned a fairly comprehensive listing of every costume my friends have bought, made, or admired in the past few years. That could help with ideas for later this month, and prompt a few conversations, too.

Some task-centric searches produced surprising results, too. “Book to read” yielded various discussion threads started by people asking their networks for recommendations, and a lot of good suggestions. “Apple recipe” and “bar Boston” similarly found photos, check-ins, and status updates that could help someone looking for culinary or travel inspiration—or suggest which friend to contact for advice. Even a search for “switch bank accounts” turned up a potentially useful comment thread in which friends shared experiences.

Trove is easy to use. Its search box performs as expected, sourcing a well-presented list of results, with large photos or maps where relevant, that can be ascending or descending date or by relevance.

Perhaps the biggest challenge is thinking of what to type into that search box for the first few times. Our brains have become adapted to the way Google works, and what generic search boxes on websites can offer. It is easy to understand that years and years of stuff shared by you and your friends on Facebook might have interesting nuggets of information. But searches usually get made to accomplish something specific, and at first it doesn’t seem to make sense to try those on a social search engine.

My experience was that only by trying a few out did it become clear that your social network can help with task-centric searches, at least for any where the opinion of a friend or friend’s friend might help.

Trove’s founder, Seth Blank, says that other early users have experienced the sensation I had of not knowing what to search for. Browsing old memories and looking for product and business recommendations are the use cases people most often converge on, he says. “We’ve had conversations with people where they actually ended up buying things,” as a result of performing a search through Trove, says Blank.

Blanks says the company is testing a version of its search engine that works on data from Foursquare, Tumblr, and Twitter accounts, too. That allows some smarter search technology to be put to work, he says. For example, a photo posted without any text on, say, Twitter might also appear on Facebook, where it attracts comments, and that helps the search engine understand what it is.

However, Trove’s biggest challenge is a strategic rather than a technology one. It relies on the grace of Facebook and others to get access to a person’s social data. Trove is already limited by Facebook’s restrictions on the rate at which a third-party service that plugs into Facebook can access a user’s data.

Blank says that he’s had “informal” talks with people at Facebook and Twitter already, with more formal discussions set to take place in the future. “There are people already in the system and playing with it,” he says.

“There will clearly be road bumps, but there is value for everyone in a neutral third party,” says Blank. “If we send people back to their pages, we are helping out the networks and we are helping users get to the right place,” says Blank.

That’s not a bad argument, but second-guessing Facebook is not an exact science. More importantly, some of the ideas Blank talks about—helping people find recommendations from friends—may well be things that Facebook wants to do for itself (see “Why Facebook’s Search Engine Won’t be Anything Like Google’s”). Trove is a good proof of concept, but it will likely need a few lucky breaks to survive long-term.

Keep Reading

Most Popular

Large language models can do jaw-dropping things. But nobody knows exactly why.

And that's a problem. Figuring it out is one of the biggest scientific puzzles of our time and a crucial step towards controlling more powerful future models.

The problem with plug-in hybrids? Their drivers.

Plug-in hybrids are often sold as a transition to EVs, but new data from Europe shows we’re still underestimating the emissions they produce.

Google DeepMind’s new generative model makes Super Mario–like games from scratch

Genie learns how to control games by watching hours and hours of video. It could help train next-gen robots too.

How scientists traced a mysterious covid case back to six toilets

When wastewater surveillance turns into a hunt for a single infected individual, the ethics get tricky.

Stay connected

Illustration by Rose Wong

Get the latest updates from
MIT Technology Review

Discover special offers, top stories, upcoming events, and more.

Thank you for submitting your email!

Explore more newsletters

It looks like something went wrong.

We’re having trouble saving your preferences. Try refreshing this page and updating them one more time. If you continue to get this message, reach out to us at customer-service@technologyreview.com with a list of newsletters you’d like to receive.