Statistics on readership and posting habits for academic blogs Although this stackexchange seems to be a little hostile towards metrics (especially when they are about research productivity), it is still sometimes fun to indulge in a little bit of arbitrary measurement and quantification. Sometimes it can help you set targets, or let you know what is possible. In this case I am curious about blogs. 

Having a web-presence is important, but how do you know if your academic blog is doing a good job?

From my own experience, I have noticed that my blog gets a lot more readership and mention than any of my papers. I usually find this encouraging, and at times it helps me increase productivity by incorporating blogging into my research work-flow and feeling like I am able to communicate with people before having complete results. Sometimes even receive feedback (although my blog is not at the level of regular commentators, and nowhere close to the comment activity I see on popular blogs that I follow).

However, getting more mention than my papers is not a fair standard. In fact, I have no standard by which to decide if I am doing an alright job blogging, and what I should aim for to improve the ability of my blog to engage other researchers or interested readers. Having some hard data is also useful for converting people new to blogging to the online community.

Are there any statistics on typical readership, posting rates, and commenting frequency for small (non-superstar) academic blogs? I would be especially interested in statistics that are broken down by area, since I expect a nutrition or cancer blog to inherently get more readership than one dedicated to Stone-duality. Of particular interest to me would be information about blogs in theoretical computer science and/or mathematical modeling.
I think it's interesting to consider the relative value to society of blog posts relative to more traditional forms of content distribution, such as book chapters, text books, journal articles and so forth.

Obtaining Benchmark statistics


RSS counts: Many blogs, particularly popular ones, show their RSS subscriber count. You can use the Explore Search feature in Google Reader to search for blogs you know. This returns the number of Google Reader subscribers. This is less than the total reader count, but it can give you a rough ball park.
Page views: Some blogs occasionally post their site statistics. Alexa can provide a very rough estimate of the popularity of a site.
Comments: It is straight forward to look at other blogs to get a sense of how many comments they typically get.


My rough rules of thumb

I've been blogging since 2008 and have kept an eye on RSS feeds and page views over timeon my own blog. I've also picked up information from other blogs that I follow.
My main observations are that it takes time to produce content, get indexed by Google, obtain RSS subscribers and so on. These would be my rough benchmarks for academic blogging. In the fields that interest me (e.g., psychology, statistics, R) I can think of specific blogs that fall in to one or other of these categories. This helps to inform the benchmark. Anyway, these are just my casual rules of thumb; of course, they aren't anything definitive.


RSS subscribers:


0 to 10: Not popular
10 to 100: Just getting started
100 to 500: Moderate levels of popularity
500 to 1000: Relatively popular
1000 to 10,000: Popular Blog 
10,000+: Superstar blog

Annual Page Views


0 to 1,000: Not popular
1,000 to 10,000: Just getting started
10,000 to 50,000: Moderate levels of popularity
50,000 to 300,000: Relatively popular
300,000 to 2,000,000: Popular Blog 
2,000,000+: Superstar blog



What does a page view mean

It is a little difficult to know what a page view means in terms of achieving broader blogging goals. Only a proportion of page views correspond to a person reading the entirety of the page. And only a proportion of those page views have any meaningful impact on the reader. In order to get a sense of what these proportions might be, I reflect on my own browsing. For example, I might be searching to diagnose a software error, do a tutorial on something, or get a review of a product. It might take a few search results to find what I'm looking for. That said, perhaps something between 1 in 10 and 1 in 2 search results provide useful results.

In summary, even if only 1 in 20 pageviews helped someone in some meaningful way, if you're getting a hundred thousand page views per year, that's still 5,000 instances of people being helped.