The widespread adaption of Social Media has resulted in generating an eminent size of datasets that are created as a result of communication between users on Social media platforms. The study of social media conversations and interactions between the social media users reveals patterns and information that is potentially very useful for business and society if utilized carefully and responsibly. The scientific domain of studying methods and techniques to collect, store, process, and visualize Social Media Data for benefit of society is called Social Data Analytics.
Just like any other field concept the digital traces of Social Media usage has its associated challenges and potential dark sides, one of which is the generation of Fake and unreliable contents on social media platforms. There have been many initiatives and debates around the globe that have emphasized and affirmed that Fake and Unreliable contents on Social Media are a huge challenge. The Fake contents on Social media channels not only are generated by end-users themselves but there is a fear that such contents can be generated with the purpose of changing the opinion of people by feeding them wrong or misleading information. This is a huge challenge because there is no simple way for common citizens to be able to differentiate between reliable, credible, and fake or unreliable contents.
The European Union has acknowledged this issue and there has recently been a first-ever Fake News Control initiative by the EU. The issue has particularly been acknowledged to be harmful by assuming its potential for exploiting it for politics and elections.
There are different research groups, public and private initiatives all over the world that are continuously working on devising methods and techniques to deal with this modern-day challenge.
It is important to mention that developing countries need to be involved and make part of such initiatives. This is a global problem and it has potential adverse effects if not handled properly by legislation as well as advancements in methods and techniques that are applicable across the globe.
NISS aims to bring different stakeholders on one platform to initiate projects that advance the field of Social Data Analytics in such a way that benefits humans and minimizes its associated side effects.