According to Bitly research studies and analysis, different social networks have their own distinct personalities. The report shows how content propagates (or “goes viral”) through social networks, particularly how the day and time posted affects the eventual amount of attention it will receive. The study evaluates the persistence of a link by calculating the half life: the amount of time at which a link will receive half of the clicks it will ever receive after it’s reached its peak.
For a particular story analyzed, says the report, (Baby otter befriended by orphaned kittens) the half life was 70 minutes, the time at which this link will receive half of the clicks it will ever receive
Looking at a second link (East Coast earthquake: 5.8 magnitude epicenter hits Virginia), shared by the Washington Post on Twitter, though the details of the traffic are different, and the scale of the traffic much larger, it demonstrated essentially the same pattern: a fast rise, and a more relaxed drop-off. Noticeably, this link had a half life of only 5 minutes, beyond which this link had seen half of the clicks it would ever see.
This link is associated with a very timely event, notes the report, as opposed to the previous link (pictures clearly interesting all the time). The study concludes that the difference in content drives the difference in dynamics of these two types of links.
An alternative theory, however, that comes up frequently says the report, is that the dynamics of the link traffic depend on where the link is posted: do links posted on facebook last longer than they do on twitter?
Studying the half life of 1,000 popular bitly links, the results were surprisingly similar, says the report. The mean half life of a link on Twitter is 2.8 hours, on Facebook it’s 3.2 hours. And via ‘direct’ sources (like email or IM clients) it’s 3.4 hours. So one can expect, on average, an extra 24 minutes of attention if posted on Facebook rather than Twitter, observes the report.
In general, the half life of a link studied is about 3 hours, unless published on Youtube, where one can expect about 7 hours worth of attention. Many links last a lot less than 2 hours; other more sticky links last longer than 11 hours over all the referrers. The conclusion of the report is that the lifespan of the link is connected more to what content it points to than on where it is posted. On the social web it’s all about what is shared, not where it’s shared
Finally, there are some significant observations regarding the importance of the timing of the posting.
For Twitter, posting in the afternoon earlier in the week is your best chance at achieving a high click count (1-3pm Monday through Thursday). Posting after 8pm should be avoided. Posting on Twitter when there are many people clicking does help raise the average number of clicks, but it in no way guarantees an optimal amount of attention, since there is more competition for any individual’s attention.
For Facebook, links posted from 1pm to 4pm result in the highest average click throughs. Links posted after 8pm and before 8am will have more difficulty achieving high amounts of attention. Facebook traffic peeks mid-week, 1 to 3pm, and fades after 4pm. Despite similar traffic counts, posting at 7pm will result in more clicks on average than posting at 8pm.
The Tumblr network shows a drastically different pattern of usage from Facebook and Twitter. One should wait until at least 4pm to post. Also postings after 7pm on average receive more clicks over 24 hours than content posted mid-day during the week. Friday evening, a no-man’s land on other platforms, is an optimal time to post on Tumblr.
Optimal Link Posting Times
Optimal Time (High Click Count)
1-3 pm, Mon thru Thursday
1-4 pm, peaking Wed @ 3 pm
After 7 pm; Friday evenings
Peak of Activity
9 am -3 pm Mon thru Thurs
Mid-week, 1-3 pm
7-10 pm Mon & Tue
Times to Avoid
After 8 pm; After 3 pm Fri
Earlier than 4 pm
Source: Bitly, May 2012
The report concludes that, “... just like your neighborhood restaurants, each social network has its own culture and behavior patterns. By understanding the simple characteristics of each social network, you can publish your content at exactly the right time for it to reach the maximum number of people... “