D5.9 – Social Analytics for the study of societal factors and policy making II
Creators: name: Usman Rashid
name: Giulio Pagliari
name: Artitaya Lophatananon
name: Tanja Tomson
name: Rostislav Kostadinov
Publisher: name: Zenodo
Year: 2024
Subjects: Social Media Analytics
Policy Making
Public Sentiment
Big Data
Natural Language Processing
Decision Support System

description: Since the importance of public opinion on social media platforms has become prominent in recent years and particularly in the COVID19 pandemic, it has been realised that policy making could be more successful when the policy makers benefit from integrating this publicly available, user-generated data through the technique of social media analytics.

Administrations around the world are engaging in initiatives to determine policies based on foresight and forward-looking approaches due to the growing impact of relevant factors from unexplored territories such as social media. As the number of social media platforms and their users grows exponentially the need to address the public sentiment towards any intervention becomes significant. It also adds value to the process of creating a new policy or improving on any existing policy as the information from social media would provide a first-hand account of the public perception about the intervention. As building a policy is a complex process with so many relevant factors intertwined and affecting different aspects of the intervention, the policy makers may welcome new tools and techniques that gather and analyse real-time information based on public sentiments on social media.

The ever-growing popularity of social media has made people somewhat dependent and the public use these platforms to express their sentiments about everything impacting their lives. This generates enormous chunks of ‘big data’ everyday which makes it an asset to explore and analyse. Understanding this data presents opportunities for the policy makers to make informed policy decisions. The conclusions drawn from peoples’ general discussions and opinions helps tapping into the collective wisdom of people, that may provide fruitful ideas to approach a problem.

The T5.4 – “Social Analytics for the Study of Societal Factors and Policy Making” in the iHelp project was conceived to create a Social Media Analyser tool based on the above-mentioned assumptions. This tool will help the policy makers gather and analyse streams of social media through multiple platforms and draw meaningful information that would help in creating a new policy or improve on the existing policies. The social media analyser tool will apply state of the art techniques i.e., Complex Event Processing (CEP), Sentiment Analysis (SA), Natural Language Processing (NLP) to the gathered datasets and present the results. The results of this information will be furnished on an intuitive dashboard integrated within the project to draw significant conclusions that will assist them to create policies regarding Pancreatic Cancer.This deliverable is the second iteration of this series of deliverables and a continuation of the previous version, i.e., D5.8 – “Social Analytics for the study of societal factors and policy making I”, which provided an overview of the Social Media Analyser tool along with the technical requirements, user scenarios and the interface. It also provided multiple user interaction scenarios to provide a sensation of how this tool could serve the purpose and needs of the target users. The document discusses the evolution of this tool over the course of the project and how this task becomes relevant in combating Pancreatic cancer.

The objective of this deliverable is to present the development of the Social Media Analyser tool since its conceptualisation. Initially, this tool was conceived as a standalone component working in isolation and outside the main architecture of this project. However, as the task progressed, it was realised that the tool should be somewhat brought within the architecture of the project, also integrated with the different other components of the project, e.g., the Decision Support System (DSS) Suite.