Dr Federico Botta
Senior Lecturer in Data Science
(Streatham) 2220
01392 722220
Overview
Hi!
I am a Senior Lecturer in data science in the department of computer science at the University of Exeter, and I am also a fellow at the Alan Turing Institute. My research aims to provide a deeper understanding of human behaviour, both at the collective and individual level, by using novel data streams. Large data sets are constantly being generated thanks to our interactions with large technological systems, such as the Internet and the mobile phone network, or they can be collected through our usage of smart phone apps and tracking sensors. I use tools from data science, network theory, behavioural and computational social sciences to analyse these data sets and investigate different aspects of human behaviour.
Recently, I have also been working on a number of projects related to how we can study the cost, accessibility and performance of public transport in the UK. I am broadly interested in how we can use better data and data science methods to improve our transport systems, and support policy makers design better transport policies.
I regularly collaborate with a number of policy makers, and I am particularly passionate about how data, data science and AI can be used to support the policy making process.
I am an academic editor for PLOS ONE and I act as a reviewer for several international journals.
I was also a co-founder and organiser of Databeers Warwick, an informal networking event for all those interested in data stories.
I am offering to supervise self-funded PhD students in the areas of:
- computational social science and data science, in particular to study human behaviour using new forms of data (such as social media or mobile phone data)
- urban systems
- behavioural data science
- data science for public policy
Publications
Copyright Notice: Any articles made available for download are for personal use only. Any other use requires prior permission of the author and the copyright holder.
| 2023 | 2022 | 2021 | 2020 | 2017 | 2016 | 2015 |
2023
- Botta F. (2023) Rail journey cost calculator for Great Britain. [PDF]
- Collins T, Di Clemente R, Gutiérrez-Roig M, Botta F. (2023) Spatiotemporal gender differences in urban vibrancy, Environment and Planning B: Urban Analytics and City Science, DOI:10.1177/23998083231209073. [PDF]
- Santana C, Botta F, Barbosa H, Privitera F, Menezes R, Di Clemente R. (2023) COVID-19 is linked to changes in the time–space dimension of human mobility, Nature Human Behaviour, volume 7, no. 10, pages 1729-1739, DOI:10.1038/s41562-023-01660-3. [PDF]
- Botta F, Lovelace R, Gilbert L, Turrell A. (2023) Packaging code for reproducible research in the public sector. [PDF]
- Sheehan N, Botta F, Leonelli S. (2023) Unrestricted Versus Regulated Open Data Governance: A Bibliometric Comparison of SARS-CoV-2 Nucleotide Sequence Databases, DOI:10.1101/2023.05.13.540634. [PDF]
- Collins T, Clemente RD, Gutiérrez-Roig M, Botta F. (2023) Spatiotemporal gender differences in urban vibrancy, Environment and Planning B: Urban Analytics and City Science (2023). [PDF]
2022
- Stella M, Vitevitch MS, Botta F. (2022) Cognitive Networks Extract Insights on COVID-19 Vaccines from English and Italian Popular Tweets: Anticipation, Logistics, Conspiracy and Loss of Trust, Big Data and Cognitive Computing, volume 6, no. 2, pages 52-52, DOI:10.3390/bdcc6020052. [PDF]
- Santana C, Botta F, Barbosa H, Privitera F, Menezes R, Clemente RD. (2022) COVID-19 is linked to changes in the time-space dimension of human mobility, Nature Human Behaviour, volume 7, pages 1729-1739. [PDF]
2021
- Stella M, Vitevitch MS, Botta F. (2021) Cognitive networks identify the content of English and Italian popular posts about COVID-19 vaccines: Anticipation, logistics, conspiracy and loss of trust, DOI:10.48550/arxiv.2103.15909.
- Bannister A, Botta F. (2021) Rapid indicators of deprivation using grocery shopping data, ROYAL SOCIETY OPEN SCIENCE, volume 8, no. 12, article no. ARTN 211069, DOI:10.1098/rsos.211069. [PDF]
- Botta F. (2021) Quantifying the differences in call detail records, R Soc Open Sci, volume 8, no. 6, DOI:10.1098/rsos.201443. [PDF]
- Botta F, Gutiérrez-Roig M. (2021) Modelling urban vibrancy with mobile phone and OpenStreetMap data, PLoS ONE, volume 16, no. 6 June, DOI:10.1371/journal.pone.0252015.
2020
- Botta F, Preis T, Moat HS. (2020) In search of art: rapid estimates of gallery and museum visits using Google Trends, EPJ DATA SCIENCE, volume 9, no. 1, article no. ARTN 14, DOI:10.1140/epjds/s13688-020-00232-z. [PDF]
- Botta F, Moat HS, Preis T. (2020) Measuring the size of a crowd using Instagram, Environment and Planning B: Urban Analytics and City Science, volume 47, no. 9, pages 1690-1703, DOI:10.1177/2399808319841615.
- Preis T, Botta F, Moat HS. (2020) Sensing global tourism numbers with millions of publicly shared online photographs, Environment and Planning A, volume 52, no. 3, pages 471-477, DOI:10.1177/0308518X19872772.
2017
- Botta F, del Genio CI. (2017) Analysis of the communities of an urban mobile phone network, PLOS ONE, volume 12, no. 3, pages e0174198-e0174198, DOI:10.1371/journal.pone.0174198. [PDF]
2016
- Botta F, del Genio CI. (2016) Finding network communities using modularity density, DOI:10.48550/arxiv.1612.07297.
- Botta F, del Genio CI. (2016) Finding network communities using modularity density, Journal of Statistical Mechanics: Theory and Experiment, volume 2016, no. 12, pages 123402-123402, DOI:10.1088/1742-5468/2016/12/123402. [PDF]
2015
- Botta F, Moat HS, Stanley HE, Preis T. (2015) Quantifying Stock Return Distributions in Financial Markets, PLOS ONE, volume 10, no. 9, pages e0135600-e0135600, DOI:10.1371/journal.pone.0135600. [PDF]
- Botta F, Moat HS, Preis T. (2015) Quantifying crowd size with mobile phone and Twitter data, Royal Society Open Science, volume 2, no. 5, pages 150162-150162, DOI:10.1098/rsos.150162. [PDF]