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Bennett Kleinberg

I am an Assistant Professor (Lecturer) in Data Science at the Department of Security and Crime Science and the Dawes Centre for Future Crime at University College London. I also hold a guest affiliation at the University of Amsterdam’s Department of Psychology.

My research is about two areas:

(1) Computational approaches to security and crime problems

With more data and a changing landscape of problems, computational techniques are an exciting way to look at exisitng and novel crime and security problems. I’m especially interested in emerging crime problems and understanding them through complex text data with techniques from natural language processing and applied machine learning.

Ideas I’m working on:

examining new (crime) problems on the Internet through text (e.g., online forums)
hybrid decision-making in uncertain, large-volume environments
keyboard dynamics as a biometric identifier

(2) Methods of behavioural data science

Before computational methods can help us understand problems better (or at scale), we need good methods and tested assumptions. I’m particularly interested in building robust methods to learn about human behaviour from text and web data. Aside from natural language processing, I’m here also interested in the tool development for computational social science including applied machine learning.

Ideas I’m working on:

automated, learning-based text anonymisation (SAGE Ocean concept grant winner)
examining the fundamental assumptions of behavioural data science (e.g. the cognition-language-behaviour nexus)
sample size estimation for machine learning in the social and behavioural sciences
researchers’ degrees of freedom in natural language processing studies

For recent talks/workshops/media coverage, see here

Some of the ongoing and past projects were funded by SAGE, RUSI/GIFCT, The Dutch Ministry of Security and Justice

Research group

PhD students

Josh Kamps

Background: Computer Science, Crime Science
Topic: Detecting cryptocurrency crime
Supervised with Dr Sarah Meiklejohn
Funded by: UCL Dawes Centre for Future Crime

Arianna Trozze

Background: Law, Policy Making
Topic: Detecting cryptocurrency crime
Supervised with Dr Toby Davies
Funded by: UCL Cybercrime Centre for Doctoral Training

Maximilian Mozes www

Background: Computer Science, Natural Language Processing
Topic: Adversarial perturbations in natural language processing
Supervised with Prof. Lewis Griffin
Funded by: UCL Dawes Centre for Future Crime

Felix Soldner

Background: Psychology, Brain & Cognitive Sciences
Topic: Detecting and mitigating online consumer fraud
Supervised with Prof. Shane Johnson
Funded by: UCL Dawes Centre for Future Crime

Daniel Hammocks www

Background: Mathematics, Data Science
Topic: Detecting emerging crimes using data science techniques
Supervised with Prof. Kate Bowers
Funded by: EPSRC

Isabelle van der Vegt www

Background: Linguistics, Psychology
Topic: Understanding and predicting threats of violence using computational linguistics
Supervised with Prof. Paul Gill (UCL)
Funded by Prof P Gill’s ERC grant ‘GRIEVANCE’

Dawes reading group

We are running a bi-weekly reading group on topics around future crime (incl. data science, policy-making). Info at https://felix-soldner.github.io/dawes_reading_group/

Dissertation projects

Past dissertation projects

Teaching

2019-2020

SECU0050 Data Science for crime scientists (3rd year, BSc in Crime Science, UCL)
SECU0057 Applied Data Science (MSc in Crime Science, UCL)

2018-2019

SECU0013 Probability, Statistics and Modelling 2 (2nd year, BSc in Crime Science, UCL) // materials + companion website.
SECU0050 Data Science for crime scientists (3rd year, BSc in Crime Science, UCL) // materials + companion website.
Crime Science (honours module, UvA)

2017-2018

Crime Science, BSc module, Institute for Inderdisciplinary Studies, University of Amsterdam, Sem. 2, 2017/2018
Deception and Lie Detection, MSc module, Department of Psychology, University of Amsterdam, Sem. 1 2017/2018
Crime Science, BSc module, Institute for Inderdisciplinary Studies, University of Amsterdam, Sem. 1, 2017/2018

2016-2017

Deception and Lie Detection, MSc module, Department of Psychology, University of Amsterdam, Sem. 1 2016/2017

2015-2016

Deception and Lie Detection, MSc module, Department of Psychology, University of Amsterdam, Sem. 1 2015/2016 )

Software

NETANOS - Named entity-based text anonymization for open science
- Anonymises bunches of text files by removing identifiable information
- de-identifies numbers, persons, locations, places, pronouns, dates and times
- Developed with Maximilian Mozes and Bruno Verschuere
- Available on npm, source code on GitHub
- Published paper in JOSS and experimental validation on OSF servers
- Accessible interface version lives on netanos.io
Naive context sentiment analysis
- Performs sentiment analysis that handles valence shifters (e.g., “really”, “not”, “hardly”, “but”) on non-punctuated or poorly punctuated data
- Code lives on GitHub
- Specific use cases:
  - data that are not punctuated at all (e.g., auto-generated YouTube transcripts)
  - data that are badly punctuated (e.g., data from blogs where punctuation is not necessarily a given)
  - very brief text data: Twitter data, for example, even if properly annotated for sentence-boundary-disambiguation, would return one or two sentiment values with other sentiment extraction packages
- Contributors: Maximilian Mozes and Isabelle van der Vegt

Brief CV

Assistant Professor in Data Science (Department of Security and Crime Science, UCL)
PhD on detecting deceptive intentions on a large scale (Department of Psychology, University of Amsterdam) [2018]
MSc in Crime Science (University College London) [2015]
BSc in Psychology - specialised in Psychological Methods (University of Amsterdam) [2014]

Links:

Review service

Scientific Reports (Nature), Memory & Cognition, Applied Cognitive Psychology, Computers in Human Behavior, Acta Psychologica, Personality and Individual Differences, Current Psychology, Cognitive Research: Principles and Implications, Crime Science

Publications

All publications can be found on my Google Scholar page.

A list updated in Oct 2019 is available here

Contact

If you are interested in doing a PhD, working as a research assistant (in London or remotely) or doing a BSc/MSc dissertation, feel free to reach out to me.