Comments
2008 in historical digital terms feels like eons ago. That was the year when I first began writing an essay about the Facebook 'Like' button; a feel-good-click-once-and-move-on action. I published it to a blog I ran at Nemo Design in 2009, and posted an updated version to the NORTH blog in 2010. It is titled Facebook Likes Are not Engaging.
Looking back at it now, I realize the premise of my essay was simple; clicking a button to show your followers a brand preference was a shallow action. It merely formed a weak link.
I was somewhat prescient when I wrote: Facebook may well be around for some time, in one form or another, yet brands and marketers should watch closely the actions it takes, and those of its users, for hints of when it takes a step in the wrong direction one too many times. Or loses its relevance.
There is nothing new about web users abandoning online social networks (OSNs) as we have seen with MySpace. Relevance though, is extremely important to the OSN user - how does Facebook remain relevant to more then one billion users?
Now we learn that as Facebook approaches the end of its first decade, researchers at Princeton University have released a paper that forecasts it will lose 80% of its peak user base within the next three years.
We have heard of the coming demise of Facebook before, but what is new about the Princeton paper is that the paper's authors used epidemiological models to explain user adoption and abandonment of OSNs. It's an interesting approach. For instance they model the adoption and abandonment in OSN's alongside diseases where there are infection and recovery phases. In their paper they consider adoption as analogous to infection and abandonment as analogous to recovery:
Other OSNs have changed their colors in the past. Friendster is one example. Friendster, formed in 2002, was considered one of the original OSNs. In 2003 it turned down a $30 million offer from Google a move that was considered a mistake at the time. It was acquired in 2009 and is now a social gaming site.
I wrote here last week about complexity theory and how the science behind it should be studied by social media community managers and the owners of online music streaming services, to help them understand the behavior of their users.
This new study shows a lot of parallels to complexity theory and complex systems science. Epidemics, mass migrations, infection and recovery, complex systems and structures, are all intertwined in nature. As the Princeton paper shows, when certain user actions are extrapolated into OSNs or into music streaming services with many commonalities, we begin to understand how online systems are not immune to "infectious diseases."
The only thing that is hard to predict is human behavior.
2008 in historical digital terms feels like eons ago. That was the year when I first began writing an essay about the Facebook 'Like' button; a feel-good-click-once-and-move-on action. I published it to a blog I ran at Nemo Design in 2009, and posted an updated version to the NORTH blog in 2010. It is titled Facebook Likes Are not Engaging.
Looking back at it now, I realize the premise of my essay was simple; clicking a button to show your followers a brand preference was a shallow action. It merely formed a weak link.
I was somewhat prescient when I wrote: Facebook may well be around for some time, in one form or another, yet brands and marketers should watch closely the actions it takes, and those of its users, for hints of when it takes a step in the wrong direction one too many times. Or loses its relevance.
There is nothing new about web users abandoning online social networks (OSNs) as we have seen with MySpace. Relevance though, is extremely important to the OSN user - how does Facebook remain relevant to more then one billion users?
Now we learn that as Facebook approaches the end of its first decade, researchers at Princeton University have released a paper that forecasts it will lose 80% of its peak user base within the next three years.
We have heard of the coming demise of Facebook before, but what is new about the Princeton paper is that the paper's authors used epidemiological models to explain user adoption and abandonment of OSNs. It's an interesting approach. For instance they model the adoption and abandonment in OSN's alongside diseases where there are infection and recovery phases. In their paper they consider adoption as analogous to infection and abandonment as analogous to recovery:
We modify the traditional SIR model of disease spread by incorporating infectious recovery dynamics such that contactBy 2017 then we may see Facebook turning into a different company. I say that because even if it is abandoned by a very large portion of its users it still holds an enormous amount of data willingly provided to the company by those users. What those datum points show will be of immense value in the future.
between a recovered and infected member of the population is required for recovery. The proposed infectious recovery SIR model (irSIR model) is validated using publicly available Google search query data for “MySpace” as a case study of an OSN that has exhibited both adoption and abandonment phases. The irSIR model is then applied to search query data for “Facebook,” which is just beginning to show the onset of an abandonment phase.
Extrapolating the best fit model into the future suggests that Facebook will undergo a rapid decline in the coming years, losing 80% of its peak user base between 2015 and 2017.
Other OSNs have changed their colors in the past. Friendster is one example. Friendster, formed in 2002, was considered one of the original OSNs. In 2003 it turned down a $30 million offer from Google a move that was considered a mistake at the time. It was acquired in 2009 and is now a social gaming site.
I wrote here last week about complexity theory and how the science behind it should be studied by social media community managers and the owners of online music streaming services, to help them understand the behavior of their users.
This new study shows a lot of parallels to complexity theory and complex systems science. Epidemics, mass migrations, infection and recovery, complex systems and structures, are all intertwined in nature. As the Princeton paper shows, when certain user actions are extrapolated into OSNs or into music streaming services with many commonalities, we begin to understand how online systems are not immune to "infectious diseases."
The only thing that is hard to predict is human behavior.
No comments:
Post a Comment