Kaushal Kurapati\’s blog

Thoughts on Search, Technology and Management

Archive for May, 2007

Mid-2007: India a Trillion dollar economy

Posted by kaushalkurapati on May 31, 2007

As per Govt. of India GDP stats and current Rupee/$ value of 40.7, India is a Trillion Dollar economy now! Remember the date – May 2007. 12 nations belong to this club now.

So what would it take to double the GDP from here on? If India grows at 9% per annum rate, it would take 8 years — 2015. I would think that once an economy hits $1T, it kicks into higher gear and things would accelerate further. So the next trillion may happen sooner — 2013-2014, say, assuming a growth of 10-11%. Crippling infrastructure (power shortage, clean water, roads, ports) could be our only brake. Agriculture: Although agriculture’s share of gdp is declining, majority of the country engages in it and so agri’s performance is key to driving up consumer-demand, which clearly is a big chunk of the GDP.


Posted in Economy, India | 1 Comment »

Bill & Steve together on stage – one for the history books

Posted by kaushalkurapati on May 31, 2007

Steve Jobs & Bill Gates were interviewed together on stage by Walt Mossberg at the “D” conference outside San Diego. This is one for the history books given the huge contributions each of them had on the technology industry. Great advice from the tech leaders regarding what makes people successful — one word “PASSION“.

“8:40 p.m.: Q.: Advice for the upcoming entrepreneur?
Gates: The idea of being at the forefront and increasing in size has been one of our greatest challenges. Our business is really about the passion.
Jobs: If you don’t love it, you’re going to fail. You’ve got to love it and you’ve got to have passion. And you’ve got to be a great talent scout, you can only build a great organization around great people.”

Being successful is all about having “passion” for what you do. This is the essence really. I have seen this in my own work; when I am passionate about what I do and really love it, thats when my best creativity comes forward. When I don’t like what I do, I don’t even come close.

Posted in Innovation, Management, Technology | Leave a Comment »

Structure of graphs and networks – part 3

Posted by kaushalkurapati on May 28, 2007

Part 1 of this series looked at Erdos and Renyi’s Random model of networks. Part 2 of the series looked at Six degrees of separation as per Milgram’s experiment. We continue here with Granovetter’s strength of weak ties and Watts & Strogatz’ clustered world approach.

Strength of Weak Ties

Mark Granovetter identified a critical element in modeling real world networks, called the strength of weak ties. In this model, we have very close ties to few friends, forming a complete graph — implying all our friends are friends of one another too (strong ties). Some members of our close-friend-circle have acquaintance relationships (weak ties) with others, who in turn have their friend circles. So the entire human network graph is connected that has lumps of close friends /strong ties, who are joined to other lumps with weak ties.

These weak ties are what help us find jobs apparently–at least better than our strong ties. The weak ties lead us to new worlds and new opportunities that we ourselves do not know of or our strongly-tied friends are not aware of. Our close friend circle is presumably aware of similar opportunities as we do…so it is unlikely to open new doors.

Contrast this with the random model of Erdos and Renyi — in that model any two arbitrary nodes are just as likely to be connected as our close friends are! That seems quite unlikely given what we know of our world. Granovetter says that social networks are not random and that our close friends form a near complete graph (strong ties) with a high clustering coefficient and we are tied to acquaintances through weak ties. 

Duncan Watts & Steven Strogatz proposed a model where people are envisioned to live on a circle. We are closed to the nodes next to us and also the ones one step away from the immediate neighbors. This network offers a highly clustered world model–like Granovetter imagined–but is also a large world model. It would take several steps to reach a node that is diametrically opposite to a node on the circle. Watts & Strogatz went on to add few random links between distant nodes on the circle. This suddenly shrunk the distance between diametrically opposite nodes and their next neighbors. Importantly a few such long-distance links are enough to reduce the overall average separation between nodes. This model then accomodates the six-degrees world view as well. Few nodes / people have distant links to people living far-off and thereby become bridges/connectors reducing hopping distance.

According to the book “this [Watts & Strogatz] model offered an elegant compromise between the completely random world of Erdos and Renyi, which is a small world but hostile to circles of friends, and a regular lattice, which displays high clustering but in which nodes are far from each other.”

Posted in Graph Theory, Math | Leave a Comment »

Structure of Graphs and Networks – part 2

Posted by kaushalkurapati on May 28, 2007

We looked at Random network model in Part 1  of this series.

 Six degrees of Separation

In 1967 Stanley Milgram, a Harvard professor, ran an interesting experiment. He chose two people in Boston as the targets. He sent letters to randomly chosen people in the midwest (Omaha, Wichita). He asked these people to send letters to these targets if they knew them directly; if not, they should send letters to their personal acquaintances, who they thought may know these targets directly. Apparently 42 of the 160 letters he sent made it back to the targets! (26%). The median number of intermediaries required to reach the target was 5.5. Rounding it up to 6 gives the famous “any two people are separated by six degrees of separation“.

This model of the world says that we live in a small world. So any two nodes in a large human network can, on average, be reached via 6 links. This does not imply reaching a node 6 links away is easy…because at each node you would have to know which out-bound link to pursue to get to your target and without that knowledge, the search quickly becomes exponential and impossible to navigate to the target.

Posted in Graph Theory, Math | Leave a Comment »

Structure of Graphs and Networks – part 1

Posted by kaushalkurapati on May 28, 2007

I have been reading “LINKED” by Albert-Laszlo Barabasi. Through a series of blog posts I will summarize my understandings of the various concepts regarding the structure of graphs and networks.

Random Network model

Paul Erdos and Alfred Renyi, both great mathematicians, assumed that complex networks are essentially random. Start with a large set of unconnected nodes and begin adding links randomly between nodes. After a while, most of the nodes will be connected and each node will approximately have the same number of links. There may be some outliers–far more links than most or far fewer links than most–but in general most of the nodes will end up with approximately same number of links. This is like a Poisson distribution.

Imagine a cocktail party with a large number of guests. You incentivize your guests to pass on a secret by introducing it to a node or few nodes. The guests have to make acquaintances to pass on the message. Will the message reach everyone? Almost all is the answer. If you plot a histogram of how many of the guests had 1, 2, …N acquaintances, the distribution will turn out to be Poisson! This is as per the random network model of Erdos and Renyi. A majority of the guests would have made the same # of acquaintances and on either sides of the peak the distribution diminishes rapidly indicating that extreme variations are very rare.

It is worthwhile to note that Erdos and Renyi did not intend to model real-world phenomenon like web-page distributions, cell-phone distributions, etc., with their random network model. They were purely interested in the mechanics of graphs.

To summarize the random network model then, it states that the average is the norm. Most people have same number of acquaintances and very few people know tons of others and very few people are compleltely isolated. This model does not answer how real world networks indeed look like. Other models were derived to explain that.

Posted in Graph Theory, Math | 2 Comments »

Mobile Web & Search Usage in US

Posted by kaushalkurapati on May 25, 2007

30% of mobile users in the US access the web from their mobile phones, according to a study by iCrossing. US cell phone subscriber base is about ~230 million (www.ctia.org). So folks accessing the web from the mobile are ~69Million, which is significant. According to the study, half of these access the web several times a week. A majority of those who access the web from theri mobile devices, 75%, conduct searches. They mainly use GYMA search engines, reflecting their PC-search choices.

Local info, weather, maps/directions form majority of the queries. Interestingly, about 85% of these mobile-web users expect mobile versions of the web sites they visit. This implies that there is a high incentive to create mobile versions of web sites.

Posted in Mobile, Search, Stats | Leave a Comment »

Search Engine Market Share: April 2007

Posted by kaushalkurapati on May 25, 2007

comScore just released Search Engine market share data for April 2007. Google inches to ~50% of the market. Yahoo, MSFT, Ask, and AOL together account for 47%. Total searches conducted in April 2007 were 7.3B, unchanged from March, but 11% up year/year.

  • Google – 49.7% share (3.6B searches)
  • Yahoo – 26.8% share (2B searches)
  • MSFT – 10.3% share (757 million searches)
  • Ask – 5.1% share (376 million searches)
  • AOL – 5% share (364 million searches)

Posted in Search, Stats | Leave a Comment »

Internet Advertising growing at 35% y/y

Posted by kaushalkurapati on May 23, 2007

IAB reports today that Internet Advertising in 2006 grew by 35% over 2005 to $17B. Display advertising grew fastest y/y at 47%; classifieds grew 44%; keyword search grew 32%. Market share breakdown:

  • Display Advertising 22% – $3.75B (y/y growth: 47%)
  • Rich media display advertising 7% – $1.19B
  • Keyword search 40% – $6.8B (y/y growth: 32%)
  • Classifieds 18% – $3.06B (y/y growth: 44%)
  • Lead generation 8%

Posted in Advertising, Internet, Stats | 1 Comment »

Mobile Search User Behavior

Posted by kaushalkurapati on May 7, 2007

Google mobile search user behavior analysis was published in this interesting paper. Some key behavioral findings were as follows:

  • Average number of words per query were roughly same b/w mobile & regular searches: roughly 2.3 words/query.
  • Surprisingly 17% of queries the authors looked at were URLs. The number is much much lower (1-2%) for regular search logs.
  • Top categories: in cellphone based searches, “adult” was the top category (>20% of searches); Entertainment (>10%), Internet & Telecom (>5%), Local Services (5%) and Games (>2%) round out the top-5. The interpretation was that since a cellphone is considered a very private device, people look for more adult content than a computer, which may be used by multiple people.
  • Top categories in PDA-based searches differed: local services (>15%) was the most preferred category due to probably the profile of the user–business users. Entertainment, Computers & Technology, Internet& Telecom, Travel, Adult, and Sports each account for ~5% of queries.
  • Query distribution: the top-1000 queries on cell phone based search accounted for 22% of all queries, whereas it was 6% for regular search. This shows that cell based search has less variety in queries currently.
  • Number of queries/session in mobile was 1.6 whereas it was b/w 2 and 3 in regular search. It takes about a minute for a user to enter a query in mobile search! This fatigue could be the reason for searching less, but being specific (same # words/query in mobile as regular search) at the same time.
  • About 32% of consecutive searches are the same; 29% of consecutive searches are refinements of original query; 14% are spellcheck triggers. So the remaining 25% are not on the same topic. This suggests that mobile search is very focussed and is not exploratory in nature.

Summary: mobile searches roughly have same # of words/query as regular search; number of queries per session is much less than regular search; people often focus their searches and explore less while mobile. It currently takes too long to input search queries, which may be limiting the # of queries/session.

Posted in Internet, Mobile, Search | Leave a Comment »