The ANU School of Politics and International Relations is proud to be welcoming Professor Kenneth Benoit as a staff member in 2019.

Ken is a world-leading scholar in the areas of quantitative text analysis methodology, party competition, legislative politics, and electoral systems. He has held positions at Trinity College Dublin and is also currently Professor of Quantitative Social Research Methods at the London School of Economics and Political Science.

We spoke to Ken below to introduce him to our university community before he arrives in February.

Q: Why did you choose the ANU/ SPIR and what are you most looking forward to working on once you get here?

The ANU School of Politics and International Relations is a fantastic community of serious researchers in political science, known internationally by work and reputation. I had a taste of this in 2015 when I spent July and August as a Visiting Fellow in the ANU’s Research School of Social Sciences. I can remember few periods as productive as that time, and look forward to a similar experience once I join in a more regular and official capacity.

I look forward to working with several staff including Ian McAllister, Keith Dowding, and Matthew Kerby on projects related to party and electoral competition and text analysis.
 

Q: What can you tell us about your research interests?

My main research in the last 15 years has been in the fields of electoral systems and party competition, especially applications for studying these using quantitative methods or novel computational approaches. I’ve been thinking deeply about measurement issues and how to evaluate policy spaces and political actors’ positions within them. This has involved using original expert surveys, applying scaling methods to opinion surveys, using statistical scaling methods on texts (especially manifestos), and using crowd-sourcing to code texts.

I have also been deeply involved in the emerging “text as data” movement in the political and social sciences, which involves using text as something not to be read or interpreted for meaning, but to be mined for other information such as the latent positions of the actors who generated the text, or their affective orientations (often termed “sentiment”), or a measure of the themes or topics covered in the text (to give just a few examples).
 

Q: What are some of the most exciting developments in this field over recent years?

This has really been the convergence of techniques and methods from related fields such as computer science and computational linguistics, and their deployment for social science research. The latent Dirichlet allocation topic model, for instance, came and has largely passed in computer science, yet has continued to undergo novel development and applications in political science where it and its descendants serve as incredibly useful tools for measuring issue attention or themes across huge quantities of text. The whole field of “big data” analysis and the fact that much of this data is unstructured text in general has meant that we need automated, fast, large-scale techniques for mining and making use of this information. Social media for instance generates hundreds of millions, or even billions, of new data every day, and the development of methods and their applications for coming to grips with this has been one of the most exciting – and challenging – developments in the field of text analysis and I think, more generally in the social sciences as well.

Ten or fifteen years ago, researchers had very limited access to fast, scalable, and trustworthy tools for big data analysis. Today, there are amazingly well-developed tools for data science, including a massively comprehensive set of libraries for the R and Python languages. I’m proud to have contributed to this on the R side, in the field of text analytics at least, through my quanteda package (for the quantitative analysis of textual data) and a related family of text analytic tools. This is moving forward at an accelerating pace, even beyond the grant that funded its initial development, as the project takes on a more structured form with more contributors. In 2018, I set up a non-profit organisation, the Quanteda Initiative, that hosts information about the software, including tutorials, documentation, news about events, and a blog. We are also actively developing YouTube video tutorials for the quanteda YouTube channel. We are close now to 200,000 downloads but the goal is to reach 1 million by the end of 2019.
 

Q: When you arrive you’ll be dividing your time between Australia and Europe, what opportunities will that present?

For me, it’s really the best of both worlds, as I have funding for my ongoing text analysis work from the European Research Council, and students and a post-doctoral researcher working with me on the development of the project. In Australia, I am already involved in the early stages of an Australian Research Council Centre of Excellence grant application, to which I would contribute expertise in text analytic methods. There is also a strong group at ANU doing natural language processing from a computer science perspective, as well as at other Australian institutions (Queensland for instance). I’m looking forward to contributing to this new community and network of scholars, and expanding my knowledge of techniques and tools, as well as learning more about the research needs of communities outside of the ones I encounter most at the LSE.

On a personal level it’s going to provide an amazing burst of productivity since I remember somehow getting more done than ever while at ANU and still having time for exploring and socializing. I like to think of it as the ultimate commuting tradeoff: I have to commute once, very far, to get to the ANU, but once there I will not have any of the daily, shorter commutes I experience in London but that carve out productive and leisure time from my day.

I also remember loving the fact that the days were mostly quiet from European and US email, until I was ready to quit in the evening.
 

Q: Finally, what Australian cultural custom are you most excited to try out?

All of them! Including throwing a lot of shrimp on the barbie. (Just joking, I know that no one says that.). Is PM-spotting a thing? Like train spotting but it’s where you try to catch glimpses of the prime ministers as they come and go.

I love the Australian airports, they are so modern, efficient, and practical. My theory is that this is because Australia is so vast, that inter-city travel requires flying. So the airports might as well be nice and efficient. I will use them to explore as much as I can, to get to know other cities and institutions as I build up a new network of colleagues.

I am also really looking forward to playing a lot of golf, and enjoying the second summer we will have during what would otherwise be a cold, windy, wet time in London. I’m also an avid photographer and will be looking to expand my experiences and portfolio while in Australia and meeting some of the local photography clubs and their activities.