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Dr James Ashford
Teams and roles for James Ashford
Research Associate
Arts, Humanities & Social Sciences
Overview
I am a Research Associate at the Security, Crime, and Intelligence Innovation Institute, specialising in areas such as data visualisation, network science, social media, computational social science, and disinformation analysis. My research aims to explore how social networks and data science can be applied to understand online behaviour and mitigate the spread of fake news. I obtained my PhD from the School of Computer Science and Informatics at Cardiff University in 2023, where I was funded by DAIS-ITA from 2018 to 2023. My expertise combines social science methodologies with advanced computational techniques to tackle challenges in social media, digital communication, and online discourse.
Publication
2022
- Ashford, J. 2022. A network science framework for detecting disruptive behaviour on social media. PhD Thesis, Cardiff University.
- McMillan, C., Felmlee, D. and Ashford, J. R. 2022. Reciprocity, transitivity, and skew: comparing local structure in 40 positive and negative social networks. PLoS ONE 17(5), article number: e0267886. (10.1371/journal.pone.0267886)
- Ashford, J., Turner, L., Whitaker, R., Preece, A. and Felmlee, D. 2022. Understanding the characteristics of COVID-19 misinformation communities through graphlet analysis. Online Social Networks and Media 27, article number: 100178. (10.1016/j.osnem.2021.100178)
2021
- Davies, C. et al. 2021. Multi-scale user migration on Reddit. Presented at: Workshop on Cyber Social Threats at the 15th International AAAI Conference on Web and Social Media (ICWSM 2021), Virtual, 07 June 2021. AAAI, (10.36190/2021.13)
2020
- Ashford, J., Turner, L., Whitaker, R., Preece, A. and Felmlee, D. 2020. Assessing temporal and spatial features in detecting disruptive users on Reddit. Presented at: 10th Workshop on Social Network Analysis in Applications (SNAA 2020), The Hague, Netherlands, 3 August 2020.
2019
- Ashford, J., Turner, L., Whitaker, R., Preece, A., Felmlee, D. and Towsley, D. 2019. Understanding the signature of controversial Wikipedia articles through motifs in editor revision networks. Presented at: The Web Conference 2019, San Francisco, CA, USA, 13-17 May 2019.
Articles
- McMillan, C., Felmlee, D. and Ashford, J. R. 2022. Reciprocity, transitivity, and skew: comparing local structure in 40 positive and negative social networks. PLoS ONE 17(5), article number: e0267886. (10.1371/journal.pone.0267886)
- Ashford, J., Turner, L., Whitaker, R., Preece, A. and Felmlee, D. 2022. Understanding the characteristics of COVID-19 misinformation communities through graphlet analysis. Online Social Networks and Media 27, article number: 100178. (10.1016/j.osnem.2021.100178)
Conferences
- Davies, C. et al. 2021. Multi-scale user migration on Reddit. Presented at: Workshop on Cyber Social Threats at the 15th International AAAI Conference on Web and Social Media (ICWSM 2021), Virtual, 07 June 2021. AAAI, (10.36190/2021.13)
- Ashford, J., Turner, L., Whitaker, R., Preece, A. and Felmlee, D. 2020. Assessing temporal and spatial features in detecting disruptive users on Reddit. Presented at: 10th Workshop on Social Network Analysis in Applications (SNAA 2020), The Hague, Netherlands, 3 August 2020.
- Ashford, J., Turner, L., Whitaker, R., Preece, A., Felmlee, D. and Towsley, D. 2019. Understanding the signature of controversial Wikipedia articles through motifs in editor revision networks. Presented at: The Web Conference 2019, San Francisco, CA, USA, 13-17 May 2019.
Thesis
- Ashford, J. 2022. A network science framework for detecting disruptive behaviour on social media. PhD Thesis, Cardiff University.
Research
My main area of research focuses on understanding how methods such as social network analysis can be used to better comprehend how social media and its affordances are leveraged to disrupt normal discourse and subversively influence individuals or groups.
My PhD thesis explores how this can be achieved through network science, using various forms of networks to represent the behaviour of actors on social media, rather than focusing on the specific content they produce.
In summary, my academic research interests include, but are not limited to, the following:
- Data Visualization
- Network Science
- Data Science
- Social Media
- Computational Social Science
- Disinformation and Fake News
- Algorithm Design
- Machine Learning and Pattern Recognition
Biography
Education
Cardiff University
PhD. Computer Science: (2018 – 2023)
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Thesis: A Network Science Framework for Detecting Disruptive Behaviour on Social Media
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DAIS-ITA funded scholarship
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Independent research performed under the supervision of Professor Roger Whitaker with the Security, Crime and Intelligence Innovation Institute – Cardiff University.
University of Bristol
Postgraduate Certificate in Engineering: (2017 – 2018)
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Completed a series of modules in the field of Data Science including Machine Learning, Computer Vision, Applied Data Science, Mathematical Uncertainty Modelling, Logic Programming, Cloud Computing, Bioinformatics, Statistics, Economics and Research Skills.
Bangor University
BSc. Computer Science (First Class Honours): (2014 – 2017)
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Thesis: Data Visualisation and Sentiment Analysis of Political Data
Contact Details
Research themes
Specialisms
- Data science
- Social Media
- social network analysis
- Data visualisation and computational design