I took a look at three specific examples to show how social platforms have shifted user behaviour but also were influenced by it.

Twitter favourites

This is a great example of how a relatively simple design change has impacted user behavoiur and caused a shift to ‘favouritism’. In December 2011, Twitter changed its site and added a feature to show you who had favourited your tweets. This was a simple change that saw a massive impact in user behavior. 

John Herman at Buzz feed noticed that a there was suddenly a steep rise in the number of favourites around ‘lets fly’ and it led to a shift in how people think about tweets. That they are objects rather than posts; units of media rather than simple links.

Many a social media marketer will see the similarity to the Facebook “like” and, as Neil Perkin suggests, a new way to say ‘Good post’. For me, the graph below highlights how one simple platform change can have a huge impact on consumer behaviour

Note: It is interesting to see SEOMOZ releasing news on its new measure of social authority based on Retweets this week.  

I don’t consider this the best metric of influence and maybe this could be left for further discussion in the comments section below. Could this be an example of a community platform trying to influence the wider community behavior?

LinkedIn 1%

Who received their LinkedIn top 1% or 5% status? In many ways a very clever campaign to encourage social sharing and play upon ego metrics and factors related to Maslow’s hierarchy of needs.

However, in many ways it can be viewed as pointless and not relevant. Either way it influenced consumer behavior immediately and people’s desire and need to share.

Kudos to Martin MacDonald of Expedia for pointing out data taken from Topsy on the correlation between the social campaign from LinkedIn and user behavior of 300-600 tweets per day suddenly jumping to 47,000 over a few days. 

Facebook Graph search

Facebook Graph search is, basically, personal big data. It’s a search engine based on your data and your network data – connections and likes – and Facebook has taken a layer of big data and built a preference engine around this that represents a new era in the development and relationship between search and social.

This also represents a  shift, not only in Facebook’s need to become even more relevant, but in consumer behavior.

Security and privacy of data has always been an issue online and Facebook’s Graph search does limit the amount of information available but it does make your personal information more available for others – friends of friends and likes.

When looking at the potential privacy nightmare, it is clear to see that this change will impact consumer behavior and what’s more, if it doesn’t, consumer behavior will dictate its success or failure.


The three examples above all give us reasons to share but also reasons not to share.

Fear, privacy and strategic goals may prevent people from over sharing of personal information in the future whilst business people begin to think and act more strategically about their use of social networks and social connections.

This could be based on a need for survival rather than just a simple formula that matches the traditional social media hypothesis to Maslow’s hierarchy of needs – Maslow rewired.

Social media networks do dictate consumer behavior but at the same time their success relies on it.