The past decade has seen the rise of social media platforms and their impact on human society. They have managed to acquire a vital role in daily life, and almost everyone is now on these platforms, spending hours a day scrolling through different content.
Now, these platforms invest a lot to improve their user experience, and they do this by assessing what is working and what is not. In this case, computational social science emerges as a great tool for this purpose.
What is computational social science?
Computational social science uses a computational approach to understand the concepts of social sciences and then formulate some new concepts out of them. Computers are used to analyse, model, and simulate social phenomena. In easier words, it would be that you are using digital data to understand human behaviour.
For that reason only, social media platforms like Facebook (and all the other allied services, including Instagram) invites PhD applications from all around the globe for the Meta PhD Fellowship. This program allows the relevant personnel of the social media platform to collaborate with these doctoral students. Both groups engage in innovative and relevant research jointly in areas related to social behaviour and computer science.
Some of these areas include how to engage users in a more positive way, how to remove the irritating features which could increase the bounce rate or how to characterise troublesome behaviour online and reduce it or eliminate it completely. This helps to enhance user engagement, improve the recommendation system and strengthen the moderation policies for leveraging the customer experience. All this is done on the basis of the data collected.
How is computational science improving the social media experience?
According to Manoel Horta Ribeiro, a PhD student and a Computational Social Scientist-cum- Facebook Fellow says that computational social science has the power to transform the way we use social media.
Safer, healthier, and kinder are the new buzzwords that can be used for tomorrow's social media. According to Ribeiro, this is an ongoing process that is still active now. The way decision systems of Social media are constantly working round the clock to improve the way people behave and how the computation social science systems weed out all the negative behaviour. The filtering is almost instant.
Once the AI and ML see the problematic behaviour of a user, it notifies the backend. If the person is a victim, their accounts are secured, and the negative comments are removed. If it is the perpetrator, they are banned from the website or their account is suspended indefinitely if the action is not criminal or with criminal intent.
What else is being studied by Computational Social Scientists?
There are many people like Ribeiro who are also studying how approvals for posts alter the method by which moderators handle groups. Some findings suggest that when post-approval is active, then there is rarely any moderation-related event. The effects of removing a person from the social media platform are effective in the short term. But in the long term, it gives rise to a new problem - the creation of new accounts or migration to other platforms.
To summarise, it is clear that computational social science is emerging as an effective tool for handling and improving the social media experience. Moreover, as AI technology improves, this process will have more development. So, if you want to know about this progress and how computational social science is making a difference in the social media experience, you can visit the blog section on the E2E Networks website.