In its second week since launch, Microsoft’s new Bing search engine has continued its steady growth, according to comScore. Bing is up about 3 percentage points in both average daily penetration among US searchers and their total share of search results pages (which indicates the percentage of all actual searches, though is not an exact measure), compared to the week prior to launch. Bing now has 16.7% searcher penetration and a 12.1% share of search results pages among all US workday searches. Those numbers are also both up compared to its first week in the wild.

Microsoft has been on an advertising blitz since their new search engine’s launch, spending a reported $80 to $100 million on a campaign to push Bing. That has, at times, ranged from clever to downright bizarre. But the early numbers indicate that Microsoft’s advertising push is at least driving a measurable number of curious searchers to Bing.

Read More: Bing Keeps Growing: Has Microsoft Finally Cracked Search?

People think about PageRank in lots of different ways. People have compared PageRank to a “random surfer” model in which PageRank is the probability that a random surfer clicking on links lands on a page. Other people think of the web as an link matrix in which the value at position (i,j) indicates the presence of links from page i to page j. In that case, PageRank corresponds to the principal eigenvector of that normalized link matrix.

Disclaimer: Even when I joined the company in 2000, Google was doing more sophisticated link computation than you would observe from the classic PageRank papers. If you believe that Google stopped innovating in link analysis, that’s a flawed assumption. Although we still refer to it as PageRank, Google’s ability to compute reputation based on links has advanced considerably over the years. I’ll do the rest of my blog post in the framework of “classic PageRank” but bear in mind that it’s not a perfect analogy.

PageRank sculpting