Pranav Bhasin

The title is a copy of a recent post by Fred Wilson, but the post is not . The part that caught my attention in the post was the statement “it’s a lot harder to spam yourself into a social graph”.

My personal view is that first of all, it is somewhat unfair to compare search with social since they solve vastly different problems. To me “Search equals Intent” whereas “Social equals Discovery“. When you really want to find something, the first thing you do is google for it. Yes, you may ask a few friends about it, but in most cases the expert on your question may not be in your network at all. You may post your question on twitter or facebook, but you certainly won’t wait on these channels for an answer.

The two things that social brings into the picture is “serendipity and trust“. If you are a part of a social network, you hear all kinds of things whether you want to hear them or not and in some cases, you do stumble upon some really neat stuff. Thats serendipity and since you heard about it from someone in your network, you know how much to trust the information based on the trust you have on the source of the information. To a large extent, this is a completely different way of getting information than what search has to offer, but certainly not good enough to kill search by itself.

That is why, at lifeblob, we are building a new channel for discovery of photos through your social graph, not trying to compete with google image search.

Whats your take on search vs social?

When google announced a preview of google image swirl I was compelled to check it out. After all lifeblob is also in the business of photo discovery and it is always good to know what other companies are doing in this area.

The preview is neatly built in flash and presents a very interesting visualization. This reminds me of a similiar visualization they did earlier for a “wonder wheel” view of navigating through search results. The part that I did not like though was that exploration ends very abruptly – perhaps this is because they are running on a limited data set and will not be a problem in the final version.

That brings me to the question – what is google trying to achieve through this? Is it just a ploy to counter the advances of microsoft in visual search or is there a bigger agenda behind this?

My verdict: There is a bigger agenda here. Read On.

1) Searching through images is not an easy task and given that google’s key focus is search, they would want to establish a big lead in the image search market as well. So far, google image search attempts to identify duplicate images so that they do not present duplicate results to the user. With this kind of a visualization however, google lets you explore variants of the same image so that you have more freedom to choose the one that fits your bill.

2) This is an excellent way to provide more visual detail around a searched topic. Imagine a wonder wheel kind of icon next to your regular search results, clicking on which opens up the image swirl widget and lets you see photos related to a search result.

3) Search is intent driven – you type in a few keywords and then choose a result that matches your intent. Google has used this information very effectively for its regular search to verify that the results being shown match the user intent and also to improve its data mining algos to continuously improve the results.

Images suffer from a terrible handicap that they don’t have any metadata to organize them and google typically relies on information around the images, tools like image labeler and some level of image analysis to understand what they are about. By presenting the results in a visualization like this and watching user interaction patterns, google will get excellent information about images and to improve their image search.

4) Navigating through images this way is very enjoyable and gets people to spend more time on google properties. Now, that may not necessarily align with their standard way of measuring search effectiveness ( its counterintuitive, but google wants you to spend as little time as possible on its search pages, which is their metric for measuring how good their results are ) but hey,  the more time they spend here, the more time they are off Microsoft’s visual search and thats a good thing . Plus, the metrics that apply for text based search may not apply for visual media search anyway.

What do you think about this?

Reuters ran an article last week talking about how traditional photo sharing services are having a run for their money because users of social networking services are happy sharing photos over there.

Very true! Infact, this is a repeat of the classic dilemma of reinvent or perish. The basic question to answer is – “Why do people share photos”? Two answers come to mind:

1) To show it to friends and family
2) For archiving, just in case you lose your hard drive full of photos

As all your friends move to social network and you get more connected online, naturally sharing photos on a social service starts making a lot of sense. Why would you want to upload your photos on another site and send links around when you can just upload your photos and the social site takes care of letting your friends know about it.

As a result photo services are left with no other option but to turn more social. However, the good news is that photos are still relatively dumb creatures and there hasn’t been much done to unleash the full power of a network of photos. So there is plenty of room for innovation and a lot of value addition that can be done to turn photo sharing into an activity, more entertaining than it has ever been.

That is what we are trying to do with photo sharing at lifeblob – building a more intelligent tool that understands how photos are connected and helps you navigate through them.

Today, I came across this post by Prof Ramesh Jain and I couldn’t agree more.

A quick peek at the most popular photo management solutions today will tell you that it is still all about uploading your photos, organizing into albums and creating a slideshow. Flickr, to some extent lets you discover related stuff through tags, but thats pretty much it.

To me, a photo management solution is about discovery, photos connecting with each other and navigating through the mesh of related photos. Add to this the time context around a photo and it has all the ingredients of a heady cocktail that could have you hooked for hours.

Imagine taking a shot of  “The Statue of Liberty” and instantly finding other people who also shot it around the same time. Or imagine going on a trek with your friends and getting a view of what your friends did while you were at the trek. Imagine attending a pink floyd concert and discovering shots taken by fans at several other previous concerts of pink floyd.

The possibilities are endless and there is a huge problem to be solved here. We are trying to crack some of these problems at http://www.lifeblob.com by making it really easy for you to add and organize your photos in a time based manner. We have also built a system that tracks connections of each photo and highlights connections that are more important to you than others.

We are in the process of turning on some discovery options like the examples that I gave above and hopefully you will be able to take a test ride of this before the end of this month.

If you also think that photo management is an unsolved problem, I would love to hear from you!