Interview with Dr. Jing Ma

Dr. Jing Ma was a final-year Ph.D. student at the Chinese University of Hong Kong when she was visiting us in January 2020 (She graduated in February 2020). Her research topics include Natural Language Processing, Rumor Detection, Stance Detection, Social Media Analytics. She has published around ten papers about fake news detection at prestigious venues like ACL, IJCAI, WWW. She was also a visitor to the NLP group at NTU for more than eight months. Previously, she worked as a research intern at companies like Tencent AI Lab, Baidu NLP.

  1. Could you explain your recent research?

My recent research topic is fake news detection. Claim verification is generally a task of verifying the veracity of a given claim, which is critical to many downstream applications. Any arbitrary claims need to be verified. We need to determine the truthfulness of each claim by using NLP techniques. In this way, we can make the internet environment to stop the fake news or rumor propagation further that mislead people’s leading in social media or news media. 

  1. What is your future research plan? 

Fake news detection still has many potential problems to solve. So I am going to make an in-depth analysis of fake news detection or claim verification. I also plan to do another interesting NLP task like hate speech or Wikipedia contents quality evaluation. 

  1. What motivated you to research with IBS, and what is the current research in IBS?

Mia is a very excellent researcher, and I would like to work with Mia. It is the main reason I research with IBS. IBS is a fantastic workplace. IBS provides enormous support to researchers and interns. After I joined IBS, I would like to find a potential research topic in which I can give some help or join the project to achieve significant progress. For now, I lead the hate speech detection, fake news detection, and Wikipedia project. Especially hate speech project in which I work with IBS is an up-and-coming project. As social media develops, more and more people express their own opinion, including hate speech, which harmful to children. We also can create a lot of works contributions based on hate speech projects. So I think hate speech project is a very significant task in the future. Studying with IBS data science group members offers many ideas about my future researches. I want to continue to study with IBS.

  1. What are the most challenging and favorite parts of your researches?

I think the most challenging problem in the NLP task is to find interesting research topics. I need to predict whether my project can survive for quite a long time. I always consider that my project to be a “seed” project so that it can bring out a lot of relevant follow-up researches. For example, in the case of my fake news detection project, few people researched this project previously. I lead a fake news detection project and give some fundamental contributions to this project so that others can do further development based on my research. I think this is my favorite and challenging part of my studies.