View Proposal

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Proposer

Wei Pang

Title

Machine Learning for Understanding Evolution of Topics and Public Attentions

Goal

Description

We try to understand topics and public concerns over time from news media or other related documents (such as patent data) and gain insights into the evolution of topics and public attention on the circular economy or green innovations. So we need to use machine learning models (e.g. dynamic topic modeling and dynamic clustering) to understand how the public's opinions are changing over time. Specifically, this is related to an EPSRC project DCEE (https://dcee.org.uk/) with Imperial and Loughborough (https://gow.epsrc.ukri.org/NGBOViewGrant.aspx?GrantRef=EP/V042432/1). One task is to understand public perception of the electrochemical circular economy through social media or large amounts of online texts. For example, what are people's views and concerns on sustainable chemical products?

Resources

Background

Url

Difficulty Level

Moderate

Ethical Approval

Full

Number Of Students

1

Supervisor

Wei Pang

Keywords

Degrees

Bachelor of Science in Computer Science
Master of Science in Artificial Intelligence
Master of Science in Artificial Intelligence with SMI
Master of Science in Computing (2 Years)
Master of Science in Data Science
Bachelor of Science in Computing Science
Bachelor of Engineering in Robotics