Physicists Find Users Uninterested After 36 Hours

SuperGrads writes "Statistical physicists working in the US and Hungary have found that the number of people reading a particular news story on the web decreases with time by a power law rather than exponentially as was previously thought. The finding has implications for the study of information flow in social networks, marketing and web design."

Re:maybe because it's not "news" anymore?

[truthsearch]

It might also be relevant that this study was done only on a Hungarian news site. It's possible there would be different results in other countries due to cultural differences and the number of available news sources.

Possible other causes?

[Todd Knarr]

One has to wonder how the site's story policy affects the drop-off. That is, is the drop-off because users are uninterested or not reading, or is it because after that time the story drops off the main pages and becomes hard to find to read?

BREAKING NEWS

[27,000]

PHYSICISTS REPORT ARTICLES NOT ON FRONT PAGE READ LESS

ALSO NOTE THAT SITES HAVE FINITE NUMBERS OF USERS

And nothing about 'uninterested users'. This implies that, well, a reader is not likely to read an article more than once. Shocking, much unlike the answer to the question who is funding these people?

Exponent? Power?

[ch-chuck]

Color me ignorant, but I thought exponentials and powers were the same thing?
Or are they talking about natural exp -vs- a higher order power, like 4 or 5?

Re:maybe because it's not "news" anymore?

[twistedsymphony]

I'm wondering if these same researches tried to define what their subjects defined as "news"? If something was newsworthy, I'm guessing they likely found out about it over time. Maybe the people didn't read it because they were informed from other sources?

Maybe that's exactly right? maybe 36 hours is the saturation point where someone is most likely to have already seen it elsewhere... After-all if YOU haven't seent it yet, it's still news to YOU.

How is this physics?

[nigham]

Physics is the science of nature, and I don't think human nature is included.

One slight problem...

[pla]

Okay, folks - Since I have yet to see any non-humor comments on this topic, I'll break the ice. From TFA:

Thanks to automatically assigned "cookies", the scientists were able to reconstruct the browsing history of about 250,000 visitors to the site over the course of a month.
[... and ...]
Although the average half-life varies for different types of sites, the decay laws identified are likely to be generic because they do not depend on content, but are manly determined by a user's visiting and browsing patterns.

So, what do we see here?

This trend depends on user browsing patterns rather than content, but also depends on users allowing cookies to live for not only longer than one browsing session, but for a full month.

Thus, much like that classic problem of proving the external validity of any research done by a college psych department on their own undergrads (which usually results in 80-90% female and at least half freshman participants), this study has a pretty glaring flaw - It only really says anything about MSIE users (and even then, only MSIE users dumb enough not to use some form of cookie management) rather than users in general. While that almost certainly includes the majority of visitors to many sites, it doesn't safely extend to the larger population of all web surfers.



Additionally, I would point out one more glaring source of error... It fails to normalize each unit of time against the remaining base of users - So, for example, if 90% of the regular visitors to a site see an article within an hour of posting, that leaves only 10% (plus the negligibly-small number that re-read the same article over and over, except on Slashdot where you can use FP refreshes as a solid measure of workday boredom). That, IMO, says far more about how long the typical (MSIE-qualified as above) user can go without a news fix, rather than how long an article remains interesting.

Summary misstates article

[Nurf]

If you read the article, it says the distribution of half-lives of stories decreases as a power law, not that hit rates on stories decrease as a power law.

Half lives are a measurement of exponential decay. Individual stories still decrease in hits exponentially over time. If you look at lots of stories, the decays are distributed according to a power law.

The article directly contradicts the Slasdot summary.

Hits on stories do decrease exponentially.

I am stunned that I am the only one so far who seems to have picked up on this. Did anyone actually read the article, or did they just read into it what they were told they would see?