Fully Funded PhD Scholarship in Individual Patterns Evolution of Social Media Interactions

Northeastern University London

Funding provider: Sony CSL - Paris

Project start date: Flexible before October 2026

Supervisors (lead):

• Riccardo Di Clemente* (Complex Connections Lab, Network Science Institute, Northeastern University London)
• Giulio Prevedello (Sony CSL - Paris)
• Andrew Hone (University of Kent)

Aligned programme of study: PhD in Network Science

About the Complex Connections Lab

The Complex Connections Lab is a research laboratory based at the NUL dedicated to studying the complex social connections that govern human behaviour and interactions in cities and online. The Lab focuses on the study of the digital traces we left behind to capture human behaviour and social dynamics through the lens of Network Science, Complexity Theory, and Data Science.

The team is made up of researchers in fields such as data science, computer science, and mathematics, that work together to develop innovative methods and tools to analyze large-scale data sets and gain insights into the underlying principles of the complex connections we live within.

About the Sony CSL - Paris

Sony Computer Science Laboratories Paris (Sony CSL - Paris) is a research centre dedicated to advancing fundamental and applied research across a wide range of fields, including music creativity, computational social science, language, and sustainable agriculture.

The Paris laboratory brings together researchers and engineers with backgrounds in computer science, physics, signal processing, and statistics. This interdisciplinary environment encourages researchers to pursue their scientific interests with a high degree of intellectual freedom and from distinctive, often unconventional, perspectives.

Sony CSL - Paris has a strong track record in securing European research funding and maintains an active network of collaborations with leading research institutions, as well as with artists working in visual arts and music. These interactions play a central role in shaping the lab’s research culture and in fostering innovative, cross-disciplinary work.

About the Network Science Institute (NetSI)

In 2023, NetSI established a new institute hub in London, UK at Northeastern University London. The new NetSI in London was created to advance research, education, and innovation centred around network science. The hub in London will also facilitate the development and growth of collaborations and partnerships within the UK and across Europe and US. The London hub, along with others in the US, is part of the NetSI Global program which is dedicated to engaging and integrating regional network science communities and partnering with regional talent, institutions, ecosystems of innovation.

The PhD student, even though based in London, will be a member of the Network Science Institute (NetSI), which has offices in Boston MA, Portland MA, and London UK. NetSI, founded in 2014, has emerged as a world leader of multidisciplinary research communities in the field of network science. NetSI brings together expertise from diverse disciplines, from the physical, information, and social sciences, with the goal to build and expand common, synthesising methodology and theory of networks, and to apply these tools to important societal challenges.

The successful doctoral student will be connected to NetSI’s vibrant community, with dozens of externally funded research programs, diverse faculty, and a uniquely skilled pool of fellow doctoral students and postdoctoral researchers across the global network.

About Northeastern University London

As part of a major investment, Northeastern University London (NU London) has multiple, fully funded PhD studentships available to accelerate its interdisciplinary research in the humanities, social sciences, and computing, maths, engineering and natural sciences. Each scholarship is fully-funded for three and a half years (UKRI rates) and includes full course fees, an annual stipend (including an additional London allowance) and associated costs, such as training.

NU London is both a UK university governed by UK higher education regulations, and the European campus of Northeastern University – a large, top-tier research intensive, Boston based institution. Founded in 1898, Northeastern received $230.7m of external research funding in 2022, and is the recognized leader in experience-driven lifelong learning. It has campuses across the United States and Canada (in Boston; Charlotte, North Carolina; Portland, Maine; Oakland, California; San Francisco; Seattle; Silicon Valley; Arlington, Virginia; the Massachusetts communities of Burlington and Nahant; Toronto and Vancouver). Whilst the PhD will be a UK qualification, students will have the opportunity to engage with and visit the Northeastern University network overseas as part of their London-based doctoral studies, providing a truly unique and highly sought-after dimension to their research training.

The Project

This PhD project focuses on the quantitative modelling of short-term collective attention dynamics in online cultural and social systems. Collective attention plays a central role in shaping cultural influence, diffusion processes, and long-term success: before engagement, retention, or impact can occur, attention must first be captured and sustained. Understanding how this happensm especially in the very early stages of exposure, is therefore a key challenge for computational social science.

While existing research has revealed robust regularities in long-term attention decay, burstiness, and competition effects across cultural domains, short-term dynamics remain comparatively underexplored. This gap is particularly relevant in a context where attention spans are shrinking and early exposure increasingly determines long-term outcomes. Empirical evidence shows that the popularity trajectory of a cultural item (such as a song or a social media post) can often be predicted with high accuracy using only the first few days of data, suggesting the existence of simple, general laws governing early collective attention. The core aim of this project is to identify, model, and test such laws.

The PhD will adopt a strongly quantitative and data-driven approach. The student will develop and evaluate mathematical and statistical models of short-term attention dynamics, drawing on tools from probability theory, stochastic processes, and statistical physics. These models will be tested across multiple large-scale datasets, including music consumption data, social media activity, and other online platforms, to assess their generality across domains. Where individual-level data is available, it will be used to validate behavioural mechanisms underlying observed collective patterns. The project also leaves room for integrating metadata, such as content features or contextual information, to study how they shape early attention trajectories.

Overall, the project offers the opportunity to work at the intersection of theory, data, and real world cultural systems, contributing both to the fundamental understanding of collective behaviour and to practical questions in cultural analytics and platform design.

The PhD position is funded by Sony, providing a stable and well-supported research environment with access to unique datasets and close interaction with an international research lab. The project offers the opportunity to pursue independent within a setting that combines academic excellence with real-world relevance.

The ideal candidate has:

• MSc (or equivalent) in Complex Systems, Networks, Data Science, Computational Social Science, Natural Language Models, Physics, Mathematics, Computer Science, or related subjects.
• Proficiency in programming languages relevant to research (e.g., Python, SQL, Julia).
• Experience with software development/maintenance tools, libraries, and frameworks (e.g., Pandas, scikit-learn, Spark, Git).
• Fluency in English, both spoken and written.
• Highly collaborative spirit, personal initiative, and genuine interest in interdisciplinary teamwork.
• Excellent personal and good communication skills.
• An inquiring mind and the desire to challenge themselves.
• Enthusiasm for interdisciplinary applied research.
• Experience of, or willingness to learn, data visualisation techniques, and vectorial image design for presentation and project websites.

The successful candidate will benefit from a brand-new campus on the banks of the River Thames next to Tower Bridge. This is an interdisciplinary, vibrant research environment with international collaborations, networking opportunities, local events, and a dedicated research space. It will form the hub of a highly experienced, multi-institution supervisory team from NU London, Northeastern University, Sony CSL - Paris, and the University of Kent.

Shortlisted candidates will be interviewed by the end of March. Candidates are welcome to contact the NU London supervisor with informal enquiries before the application deadline: riccardo.diclemente@nulondon.ac.uk

Eligibility

• Bachelor's degree in a relevant subject - 2:1 or 1st (essential)
• Master’s degree in a relevant subject (optional)

English Language requirements:

If applicable – IELTS 6.5 overall (with a score of at least 6.5 in each individual component) or equivalent.

Nationality

Applications are open to UK and international students. Please indicate if you are likely to require a visa on your application. We are unable to support visa costs.

Funding

This scholarship covers the full cost of tuition fees, an annual stipend and an additional London allowance (set at UKRI rates) for 3 years. For the 2025/2026 academic year the annual stipend is £20,622. Annual increments will be in line with UKRI rates.

International travel

Students will have the opportunity to optionally travel to Northeastern University in North America to further their research training and experience.

How to Apply

Please send a CV and a Covering Letter stating how you meet the requirements and why you are interested in the proposed research project by clicking on the 'Apply' button above. Please reference your application 'R139005'.