School of Electronics, Electrical Engineering and Computer Science
& ECIT Global Research Institute
Proposed Project Title: The Science of Virality in Social Media
Principal Supervisor: Deepak Padmanabhan Second Supervisor: Anna Jurek
With the high penetration of social media in everyday life, we are exposed to all kinds of information, presented in a variety of different ways. The range of feelings that they evoke are from a very broad spectrum – some of them are appear sensational, some appear surprising, amid other kinds such as informative, and newsworthy such as real-time event updates. Social media, being a completely digital entity, presents an immense opportunity to mine the digital footprint that it generates through advanced Machine Learning and AI methods.
In this project, we seek to address a variety of questions that relate to how information propagates on the web, and whether there is a secret recipe that people use to ensure that the content they generate reach a wide audience. In particular, we are interested in the nature of content that goes viral, and how it relates to other aspects of life. Are users who hold a particular political perspective more susceptible to believing in and re-sharing viral content of doubtful trustworthiness? Are there organizations or people who use the nature of information propagation on the web, to further their agenda by passing on propaganda? In summary, we seek to develop a deeper know-how of the nature of information propagation on the web, and leverage that to understand a variety of questions concerning human behaviour.
In this project, we will develop data-driven methodologies to address each of the research questions outlined above. The focus would be on developing AI and Machine Learning algorithms that can sift through the data and identify patterns of behaviour that hold critical evidence towards understanding information propagation and virality in social media.