The QMRG Committee of the Royal Geographical Society (RGS) organised a session for early-career quantitative geographers at this years RGS Annual Conference. The session was organised the PGR reps of the committee, Ruth Neville and Yue Li, and brought together a group of PhD researchers to showcase new and emerging work in the field of quantitative geography. The session consisted of four presentations from Matt Mason, Daniela Marino Castro, Jade Zhao and the CASA City Modelling Lab (made up of Claude Lynch, Maria Wood, and Thomas Murat).
Each year as part of the Early Career session we have the pleasure to award the Robin Flowerdew Prize for Best Postgraduate Paper. The prize is named in honour of Prof. Robin Flowerdew who made considerable contributions to quantitative methods in Geography, as well as having played an important role in promoting and supporting QMRG. The prize is a £100 cash prize and seeks to recognise exciting and innovate work from emerging scholars.
We are pleased to announce that this year we have awarded the prize to Matt Mason from the Geographic Data Science Lab at the University of Liverpool. Matt Mason’s presentation, “Understanding the Local Spatial and Temporal Patterns of Attitudes Towards Immigration Using Twitter Data”, offered a compelling analysis of anti-migrant sentiment on social media. By skilfully examining tweet counts and revealing how these sentiments are intensifying over time, his work highlights crucial trends in public attitudes. The use of Twitter data provided a powerful lens for understanding the dynamics of immigration discourse, and the research made a valuable contribution to our understanding of both local and temporal shifts in public opinion.
We also want to give an honourable mention to Daniela Mariño Castro for her presentation ‘Revealing Cross-Regional Patterns: The Role of Landscape in Shaping Positive Perceptions’.
All presentations showcased exciting and innovative methods on important and timely topics, proving how bright the future of quantitative geography is. The QMRG committee and session organisers want to thank all the presenters for their work and contributions to the session.
Figure 1. From Left to Right: Jade Zhou, Daniela Mariño Castro, Ruth Neville, Matt Mason, Maria Wood, Claude Lynch, Thomas Murat
Matt Mason, Geographic Data Science Lab, University of Liverpool (WINNER)
My presentation (entitled “Understanding the local spatial and temporal patterns of attitudes towards immigration using Twitter data”) focused on the results of the first research paper of my PhD. This paper looks at how sentiment towards migration expressed on Twitter in the UK changed between 2013 and 2022 and its spatial patterns during this time. I find that whilst overall average sentiment did fluctuate during this period, the biggest change was in the intensity of tweets. I find that tweets became more likely to exhibit stronger sentiments over the study period, particularly after the UK’s 2016 referendum on membership of the EU. In terms of the geography of tweet sentiment, I find that areas with higher proportions of young people, those with university level education and with more experience of migration tweet are the source of more positive tweets about migration.
Overall, my findings show the potential for digital trace data to examine the temporal and spatial patterns of attitudes towards migration and highlight the areas most likely to produce negative online content about migration. Moreover, my paper makes a timely contribution to the literature on sentiment towards migration given the recent anti-migrant and Islamophobic riots in the UK and the success of anti-migrant political parties across much of Europe.
It was my first time attending a QMRG session in person and I really enjoyed the experience. It was great to share my research in such a friendly environment and to see the exciting research being undertaken by other PhDs. The session also provided me a good opportunity to meet early career researchers and make connections with others interested in quantitative methods. I would recommend future QMRG ECR sessions to PhDs interested in quantitative geography looking for a relaxed setting to present their work or to hear about interesting upcoming research.
Email: Matt.Mason@Liverpool.ac.uk X: @mattgmasn
Daniela Mariño Castro, Department of Geography, University of Zurich - ZH (HONOURABLE MENTION)
In the project “Revealing Cross-Regional Patterns: The Role of Landscape in Shaping Positive Perception,” Daniela Mariño, a PhD candidate in the Department of Geography at the University of Zurich, Switzerland, develops methods to quantify human-nature interactions. As a quantitative geographer, her research aims to understand how hedonic well-being is perceived in landscapes at different scales using natural language models. She explores how landscapes influence positive emotional responses by analysing over 6 million crowdsourced descriptions of UK national parks.
This method assesses the tangible and intangible benefits of landscapes through automatic detection using natural language processing (NLP), gazetteers, lexicons, and finite state transducers (FST). The results provide a geolocated dataset of positive expressions linked to specific landscape aspects. For example, expressions like “the lush greenery of hills” or “the peaceful waves of the ocean” reveal spatial associations with activities, aesthetics, features, places, and time.
The outcome presents a spatial distribution of pleasurable experiences and patterns across regions, focusing on national parks and land cover. This research provides insights into how landscapes shape perceptions, serving as a starting point for further analysis in valuing Cultural Ecosystem Services. The findings also reveal patterns at different spatial granularities, delivering valuable information for land managers about what is valuable, where, and why. Additionally, it can expose potential disparities and conflicts relevant to conservation efforts and policy compliance.
Email: daniela-veronica.marino-castro@geo.uzh.ch Web: https://www.geo.uzh.ch/en/units/gco LinkedIn: https://www.linkedin.com/in/geographisches-institut-uzh X: @dmarinoc
Jade Zhou, School of Geographical Sciences, University of Bristol
I am a PhD student at the University of Bristol, researching the relationship between digital inequalities and socioeconomic conditions through the lens of e-commerce. My presentation at the RGS ECR session primarily focused on the influence of socioeconomic factors on the unequal distribution of e-commerce, represented by Taobao villages in China, using multilevel modelling. The ECR session was quite welcoming, and we had some really engaging discussions. More importantly, listening to others’ work and interacting with fellow PGRs provided me with new ideas and gave me a clearer sense of what makes a good presenter. I also thoroughly enjoyed attending the RGS conference, which was a fantastic event for geographers to connect. The conference organisers were friendly and thoughtful, contributing to the success of this large gathering. Overall, both the ECR session and the wider RGS conference were filled with wonderful memories.
Email: jiao.zhou@bristol.ac.uk
CASA City Modelling Lab – Claude Lynch, Maria Wood, Thomas Murat, CASA, University College London
Email: claude.lynch.15@ucl.ac.uk; maria.wood.23@ucl.ac.uk; thomas.murat.12@ucl.ac.uk X: @edmund__hyde; @wouldmariadoit
The CASA City Modelling Lab is a small but growing set of researchers operating out of the Bartlett’s Centre for Advanced Spatial Analysis at UCL. We presented as a trio at the QMRG Early Careers session and spoke about the three strands of research we have spun up around the theme of agent-based modelling in transportation. Agent-based models take the traditional transport modelling paradigm in a new direction, by focusing on simulated individuals as opposed to flows (as is the case in more old-fashioned models).
Because we all come from different academic backgrounds, we approach the topic in different ways. Maria looks at car dependency and electrification in relation to the climate crisis, and the way we might measure forms of ‘flexibility’ in transport through such a model. Tom aims to ‘flip modelling on its head’ by inviting machine learning into the analysis of transport scenarios. Claude refuses to touch a model and instead critically inspects what transport models achieve in practice, and how regional as opposed to national governance in transport planning affects that question.
We all enjoyed the session hosted by the QMRG and felt that it united a broad swathe of different forms of quantitative research, maintaining a critical eye on the data throughout. As a team we feel that it is important to encourage thoughtful quantitative approaches in geography; in contrast to engineering, or even planning, QM is still a growing space that needs nurturing, and we are happy to be a part of that.