Research


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I am currently a 3rd year PhD candidate at the Australian Centre for Astrobiology (ACA) at the University of New South Wales, Australia. My research concerns gathering empirical evidence for the processes, impact and outcomes of social media science communication by means of computational techniques. The science topics that I am focusing on are space science and climate change related. Given the amount of time, money and effort spent on social media science communication, it strikes me as odd and particularly curious that little concrete evidence has been provided in terms of the effectiveness of these activities. I am especially interested in the effects of social media engagement on public trust in science. Does online engagement with scientists improve public trust in science? How do we communicate science better on social media to build public trust? These are the questions I aim to answer.

I have a special interest in big data and the potential to glean meaningful insights from them to inform decision making. As I have a background in engineering and computer science, I decided to use machine learning to approach my research questions. The techniques that I have used include supervised and unsupervised learning, sentiment analysis and topic modelling. I wrote a blog post to explain my findings so far and linked to the source code for my experiments. Ultimately, I am interested in using the knowledge and results gained from my analysis to develop intuitive and useful tools to help scientists communicate their research to the public.

In a previous life I was a European Commission funded Marie Curie Fellow at the European Organisation for Nuclear Research (CERN), working as a data acquisition engineer for the Compact Muon Solenoid (CMS) experiment of the Large Hadron Collider (LHC) accelerator. The CMS collaboration is one of the two experiments that detected the Higgs Boson, a discovery that won its eponymous predictor Professor Peter Higgs a Nobel Prize in Physics in 2013.

My Google scholar profile can be found here.

 

Publications

Hwong, Y. L., Oliver, C., Van Kranendonk, M., Sammut, C., & Seroussi, Y. (2017). What makes you tick? The psychology of social media engagement in space science communication. Computers in Human Behavior, 68, 480-492.

Hwong, Y. L., Kusters, V. J., Willemse, T. A., Keiren, J. J.A., Leemans, S. (2013). Formalising and analysing the control software of the Compact Muon Solenoid Experiment at the Large Hadron Collider. Science of Computer Programming, Volume 78, Issue 12 (pp. 2435-2452).

Hwong, Y. L., Kusters, V. J., & Willemse, T. A. (2011). Analysing the control software of the compact muon solenoid experiment at the large hadron collider. In International Conference on Fundamentals of Software Engineering (pp. 174-189). Springer, Berlin, Heidelberg.

Hwong, Y. L., Willemse, T., Kusters, V., Bauer, G., Beccati, B., Behrens, U., … & Cano, E. (2011). An analysis of the control hierarchy modelling of the CMS detector control system. In Journal of Physics: Conference Series (Vol. 331, No. 2, p. 022010). IOP Publishing.

 

Refereed Conference Proceedings

Hwong, Y. L., Oliver, C., Van Kranendonk. (2017). We Engage, Therefore They Trust? A Study of Social Media Engagement and Public Trust in Science. American Geophysical Union Fall Meeting 2017. New Orleans, LA, USA

Hwong, Y. L., Oliver, C., Van Kranendonk. (2017). To Trust or Not to Trust? What Drives Public Trust in Science in Social Media Engagement. American Geophysical Union Fall Meeting 2017. New Orleans, LA, USA

Hwong, Y. L., Oliver, C., Van Kranendonk, M., Sammut, C. (2017). Keep it real and visual: dissecting social media engagement and its potential to influence trust in space science. Astrobiology Science Conference 2017. Phoenix, AZ, USA

Hwong, Y. L., Oliver, C., Van Kranendonk, M., Sammut, C. (2016). What Makes You Tick? An Empirical Study of Space Science Related Social Media Communications Using Machine Learning. American Geophysical Union Fall Meeting 2016. San Francisco, USA.

Hwong, Y. L., Oliver, C., Van Kranendonk, M., Sammut, C. (2016). Will this tweet be retweeted? An empirical study of astrobiology related social media communications using machine learning. Australasian Astrobiology Conference 2016. Perth, Australia.

 

Conference presentations

Hwong, Y. L., Oliver, C., Van Kranendonk. (2017). To Trust or Not to Trust? What Drives Public Trust in Science in Social Media Engagement. American Geophysical Union Fall Meeting 2017. New Orleans, LA, USA. Invited speaker, Fall Meeting Union lightning session.

Hwong, Y. L., Oliver, C., Van Kranendonk. (2017). We Engage, Therefore They Trust? A Study of Social Media Engagement and Public Trust in Science. American Geophysical Union Fall Meeting 2017. New Orleans, LA, USA. Oral presentation.

Hwong, Y. L., Oliver, C., Van Kranendonk, M., Sammut, C. (2017). Keep it real and visual: dissecting social media engagement and its potential to influence trust in space science. Astrobiology Science Conference 2017. Phoenix, AZ, USA. Poster presentation.

Hwong, Y. L., Oliver, C., Van Kranendonk, M., Sammut, C. (2016). What Makes You Tick? An Empirical Study of Space Science Related Social Media Communications Using Machine Learning. American Geophysical Union Fall Meeting 2016. San Francisco, USA. Oral presentation, winner of AGU Outstanding Student Presentation Award.

Hwong, Y. L., Oliver, C., Van Kranendonk, M., Sammut, C. (2016). Will this tweet be retweeted? An empirical study of astrobiology related social media communications using machine learning. Australasian Astrobiology Conference 2016. Perth, Australia. Oral presentation.