Many of us remember the origins of social media, where we connected with friends and family whilst posting photos – sometimes of our lunch – and a brief caption.
Organisations (commercial, government, NFP) learned to market to such audiences primarily via Facebook and Twitter.
Over time our usage then moved to the next phase which attracted content creators, influencers and followers.
As influencers became popular, social media moved to the next generation with the advent of platforms such as TikTok and other short-form video-sharing applications becoming popular.
Some would say these newer platforms have democratised the process of content creation, allowing anyone to broadcast their life, and maybe gain some fans.
This has posed a challenge to advertisers who seek to tap into this era of individualism where people are developing content to earn social capital and create a personal brand in order to move up the social ladder.
Some users on these sites have monetised their personal branding into professional success, though recently Instagram has attempted to defeat this by removing the public view of post ‘likes’.
The social media companies are slightly vexed by this. They want users constantly on their platforms, yet they want to be able to control advertising and associated commerciality.
An example of this is Facebook making a major play in positioning themselves as a central cloud backend for IoT.
IoT apps have surged with the creation of smart home technology, and this will be continued as the home becomes more interactive – something which our social media apps will want to be at the forefront of.
Over time, people will not direct devices. Rather, devices will tell the people in the house what they should do.
A similar thing will happen with healthcare with more and more wearable devices being created. IoT devices – and by default social media apps, if this trend continues – will collect and use more data about users and their devices.
The use of machine learning to monetise this data will be the essence for commercial success.
This will complicate securing the next generation of social media sites.
IoT ecosystems with the right blend of values and features need to be created.
New scientific methods and practical tools which analyse legitimate and suspicious behaviours of the blend between IoT and social media data – involving IoT telemetry data, human data and network data – should be the main focus of developers.
We need new standards, policies and consumer education for Australians to make informed decisions on how they should participate in the ever-expanding convergence of our online and offline lives.
Nigel Phair is Director, UNSW Canberra Cyber.