What is social media profiling?

Collected data can encompass a wide range of data points such as personal interests, behaviours, demographics and social connections.

To understand the scope of available data, consider that 20.8 million Australians maintain a presence on an average of 6.6 social media platforms each month.

While the process can yield valuable insights for businesses, it also raises multiple ethical and privacy-related concerns for the subject of profiling.

How does social media profiling work?

In general, social media profiling has distinct stages and starts when a user enters someone’s email or phone number into an intelligence tool.

Data collection

The tool scours the internet for any social media account associated with the user (such as on Instagram, TikTok, Twitter or Facebook).

Information from these sources such as text, photos and videos is then combined to provide a more complete overview of the target.

Data is also obtained on the individuals:

• Like, share and comment behaviour (to understand their interests and interactions).
• Demographic data such as age, gender, location, occupation and education.
• Interests, hobbies and other affiliations.
• Friends and followers (to understand the user’s social network, connections and influence), and
• Group memberships – the pages, groups or communities the user is a part of.

Data analysis

Tools are then used to help the user identify patterns in the social data that reveal details about the target’s beliefs, interests, habits and relationships.

Here are some of the ways the data can be analysed to do just that.

Behavioural analysis

• Engagement patterns – how often (and to what extent) users engage with content to determine their activity levels and peak usage times.
• Sentiment analysis – where natural language processing (NLP) is used to estimate the sentiment (positive, negative or neutral) of posts and comments.

Demographic insights

• User segmentation – targets can be categorised based on demographic data such as age, gender and location to craft tailored marketing strategies.
• Behavioural trends – where trends and patterns are identified in different demographic segments.

 Psychographic profiling

• Interests and hobbies – users can infer the interests and hobbies of an individual based simply on the type of content they share and engage with.
• Values and beliefs – similarly, values and beliefs can be ascertained via the analysis of posts and group memberships.

Social media profiling personas

Insights from the data analysis stage are then combined to form a persona. Think of personas as a fictional representation of an individual who, in a business context, may be the ideal customer or be part of the target audience.

In addition to details such as age, gender, hobbies and location, businesses may also build out the persona with information related to:

• Goals, motivations and desires – for example, a potential customer may want to find a safe and simple app to start investing money.
• Buying triggers – such as watching a YouTube review.
• Pain points – perhaps the individual is overwhelmed with investment advice or is concerned that they won’t have enough money to pay off student debt.

What are these personas used for?

Social media personas may be used for a variety of purposes.

Perhaps the most obvious application is in marketing, where they are used to enhance user engagement and increase conversion rates.

Social profiling also furthers demographic and psychographic segmentation to develop hyper-targeted marketing campaigns that address customer needs and resonate with their various personality traits.

Other applications include:

• Research and development – for businesses that want to use insights from market trends and emerging needs to inform their product development and strategy.
• Human resources – HR teams can also analyse a job candidate’s social media history to determine suitability during the recruitment process. Around 70% of companies vet candidates in this way with AI playing an increasingly prominent role.
• Fraud prevention – while cybercriminals often exploit publicly available information on social media, social media profiling can also be used against them. Essentially, businesses amalgamate all public information about a person and verify that they are who they claim to be. For deeper analysis, profiling can be combined with fingerprinting – a fraud prevention technique where a unique identifier is created for a user’s device and behaviour to identify inconsistencies.

Limitations of social media profiling

Social media profiling is legal in the sense that it uses information the owner has consented to be made public.

However, the use of social media data for any purpose raises ethical concerns in terms of privacy and informed consent, with most users unaware that they have “participated”  in the profiling process.

Data security can also be an issue. Companies that use social media profiling for marketing tend to create large databases of information, but these are prime targets for hackers who use the information as part of a scam to steal someone’s identity.

Lastly, the prevalence of AI in social media profiling increases the likelihood that an algorithm may misinterpret data and make an incorrect decision. This can result in missed opportunities for an individual. For example, an applicant may not progress to the interview stage of a recruitment process despite being qualified for the role.

Summary:

• Social media profiling involves the collection and analysis of data from social media platforms to create a detailed profile of an individual or group. This profile can include a wide range of information such as demographic data, behavioural data and sentiment and opinion analysis.
• Social media profiles can be adapted to form personas that are later used in highly targeted marketing strategies. Other applications include fraud prevention, job candidate screening, and research and development.
• Despite the legality of social media profiling, there are ethical concerns around the practice. Data security and the ability of AI to make merit-based decisions also require consideration.