-
Creighton, Mathew J. Hidden Hate: The Resilience of Xenophobia, New York: Columbia University Press (2023). <(opens in a new window)ISBN: 9780231203166 [Hardcover]; 9780231203173 [Paperback]; 9780231554909 [E-book]>
-
Capistrano, Daniel, Mathew J Creighton and Ebru Işıklı. “‘I guess we are from very different backgrounds’: Attitudes towards Social Justice and Intergenerational Educational Mobility in European Societies.” Social Indicators Research (2023) online, pending assignment to an issue. <(opens in a new window)https://doi.org/10.1007/s11205-023-03249-9>
-
Creighton, Mathew J, Daniel Capistrano and Monika da Silva Pedroso. “Educational Mobility and Attitudes toward Migration from an International Comparative Perspective.” Journal of International Migration and Integration (2023) 24: 817-841. <(opens in a new window)https://doi.org/10.1007/s12134-022-00977-8>
-
Creighton, Mathew J and Amaney Jamal. “An Overstated Welcome: Brexit and Intentionally Masked Anti-immigrant Sentiment in the UK.” Journal of Ethnic and Migration Studies (2022) 48:5, 1051-1071 <(opens in a new window)https://doi.org/10.1080/1369183X.2020.1791692>
-
Creighton, Mathew J, Éamonn Fahey and Frances McGinnity. “Immigration, Identity and Anonymity: Intentionally Masked Intolerance in Ireland.” International Migration Review (2022) 56(3): 881-910. <(opens in a new window)https://doi.org/10.1177/01979183211054806>
- Creighton, M., Capistrano, D., Sorokowska, A., & Sorokowski, P. (2021). (opens in a new window)Physical Spacing and Social Interaction Before the Global Pandemic. Spatial Demography, 1-10.
- Fernandez de Arroyabe, J. C., Schumann, M., Sena, V., & Lucas, P. (2021). (opens in a new window)Understanding the network structure of agri-food FP7 projects: An approach to the effectiveness of innovation systems. Technological Forecasting and Social Change, 162, 120372.(opens in a new window)
- Sanford, M., Painter, J., Yasseri, T., & Lorimer, J. (2021). (opens in a new window)Controversy around climate change reports: a case study of Twitter responses to the 2019 IPCC report on land. Climatic Change, 167(3), 1-25.
- Carol, S., Kuipers, C., Koesling, P., & Kaspers, M. (2021). (opens in a new window)Ethnic and Religious Discrimination in the Wedding Venue Business: Evidence from Two Field Experiments in Germany and Austria. Social Problems.
- Dinh, R., Gildersleve, P., Blex, C., & Yasseri, T. (2021). (opens in a new window)Computational courtship understanding the evolution of online dating through large-scale data analysis. Journal of Computational Social Science, 1-26.
- Blex, C., & Yasseri, T. (2020). (opens in a new window)Positive algorithmic bias cannot stop fragmentation in homophilic networks. The Journal of Mathematical Sociology, 1-18.
- Ternovski, J., & Yasseri, T. (2020). (opens in a new window)Social complex contagion in music listenership: A natural experiment with 1.3 million participants. Social Networks, 61, 144-152.
- Feliciani, T., Moorthy, R., Lucas, P., & Shankar, K. (2020). (opens in a new window)Grade Language Heterogeneity in Simulation Models of Peer Review. Journal of Artificial Societies and Social Simulation, 23(3).
- Gusciute, E., Mühlau, P. & Layte, R. (2022). Discrimination in the Rental Housing Market: A Field Experiment in Ireland. (opens in a new window)Journal of Ethnic and Migration Studies, 48:3, 613-634.
- Gusciute, E., Mühlau, P. & Layte, R. (2022). One Hundred Thousand Welcomes? Economic Threat and Anti-immigration Sentiment in Ireland, (opens in a new window)Ethnic and Racial Studies, 45:5, 829-850.
Today the vast amount of digital data produced as a byproduct of our daily activities on digital platforms are harnessed and analysed using advanced statistical methods and machine learning to answer old and new social science questions. In addition, online experiments have become a key methodological tool in social science, which has resulted in notable opportunities to address core sociological questions. These innovative methods, advanced within quantitative and computational social science (QCSS), are actively expanding and re-shaping sociological enquiry. The QCSS research group studies innovation, environment-society interactions, crowd-sourcing, social discrimination, collective intelligence, conflict and collaboration, the sociology of machines, and online dating - among other topics. We use methods such as agent-based and mathematical modelling, large-scale quantitative surveys, network analysis, machine learning, and online, field, and natural experiments.
- (opens in a new window)Dr Ebru Esikli (Postdoctoral Research Fellow)
- (opens in a new window)Chenlong Wang (Phd student in Complex systems and Computational Social Science)
