The LinkedIn Algorithm: How it Works
By Joshua BoydDec 13th
Published March 14th 2017
The research industry is changing. Traditionally research was based on statistics, surveys and focus groups. With the introduction of social intelligence there is now another dataset added to the mix. However, this has raised some concerns for analysts.
Is the data gathered via social representative and accurate?
Social research is different to many other research methods as it is unprompted data – it’s a new and refreshing angle.
Social analytics sits between quantitative and qualitative methods and compliments both. With social intelligence platforms you can collate the conversations of thousands of users but still get granular with the data looking at individual mentions or demographic groups.
Any form of consumer research is at best a version of the true experiences of groups of individuals.
It is impossible for any one method to perfectly encapsulate and understand complex human experiences. The more sources you add to your research mix the more accurate your data will become. Social shouldn’t be your only dataset, nor should it replace traditional methods, but complement them.
By using other datasets it is also easier to validate your results and disprove the theory that social insights are “quick and inaccurate”.
There is a concern that social data is skewed towards young adults. However, research into internet usage found that 87.9% of adults in the UK have recently been online.
User demographics can change depending on the device being used and the sites they visit, it’s important to consider this when collating the data.
Arguably no raw dataset is representative but through segmentation of data you can create a bespoke audience for your research.
An example of this could be for a fashion brand wanting to target teenagers. The social data gathered can be segmented by age, using key terms in social posts or bios. This dataset can then be benchmarked against a control group of all ages to see how the data differs from the general population.
Another way to make sure your data is representative is to weight it. For instance you could get a breakdown of the UK population and then match this to your online panel to make sure that it is representative of everyone.
When discussing representation online we also need to talk about the most common platforms of social data, Twitter and Facebook.
Twitter is mainly an open platfrom with many users choosing to keep their profiles open, however it doesn’t represent everyone and all markets. In comparison Facebook probably represents most people however it is more closed with private profiles.
Therefore, researchers may need to consider other sources which provide a better representation of their target group.
With both traditional and new research methods there are always concerns surrounding accuracy. The flexibility of social data means that different datasets can be added with ease.
The more datasets you have in your research mix the more accurate your data will become.