2012 MRes projects
- Twitter and Crime: The spatio-temporal link between social-media and criminal activity
- To what extent do water treatment processes affect the concentration of peroxide explosives in river water?
- Dual-band Frequency Reconfigurable Antennas
- Incorporating Nanostructures to Enhance the Performance of Semiconducting Metal
- A relevance study determining the use of GSR upon clothing and shoes as an item of evidence
- Automating the conceptual analysis of large-scale text-based subjective data sets
- Assessing the potential of e-noses for illicit drug detection in future drug-trafficking interdiction strategies
- Judgement in UK fingermark recovery: room for development?
- Modelling the allocation of crowd control resources
- Comparative study of the different feature extraction algorithms used for fingerprint identification
- Domain Adaptation of Statistical Classifiers for Security-related Bug Reports
- The detection of clandestine methamphetamine laboratories using semiconducting metal oxide gas sensors
- The evaluation of geochemical analysis methods for forensic provenance and interpretation
- Confirmation bias: A Study of biasability within Forensic anthropological visual assessments on skeletal remains
- Statistical change point detection of internet traffic
- Trace evidence dynamics: assessing the transfer and persistence of microbial diatom evidence in forensic investigation
- Data Communication for Underwater Sensor Networks
- Automated Cargo Inspection: Exploring the use of Machine Vision in X-ray Transmission Imaging
- Network Externalities and Migration: An Agent-Based Model Distinguishing Documented and Undocumented Flows
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Automating the conceptual analysis of large-scale text-based subjective data sets
21 March 2013
A common starting point of research in social sciences is grounded theory analysis. Through the use of some initial qualitative data-gathering, such as questionnaires and interviews, concepts and theories are discovered. As this analysis is done by hand, there is a trade-off between the time-consumption of the analysis and the completeness of concepts found. Using computational tools for this analysis can enable the researcher to gather a more comprehensive picture with little effort. The aim of this dissertation is to develop and test a framework that allows for automatic conceptual analysis of subjective subject-specific data. The initial research hypothesis follow this aim: Does the automatic computational analysis reveal the same/more insight into the security issues at the organisation than the manual approach? Is it possible to infer some underlying sentiment to each of the interviews? Can this be correlated to other features of the interview? The research group around one of my supervisors, Angela Sasse, has conducted interviews with employees of two organisations on the topic of security. The corpus consists of 118 transcribed 30-40 minute interviews from company A and a slightly smaller set of interviews from company B, about 400,000 words in total. The data has been anonymised. We hope that the outcome of this research will allow a more accurate and foremost less time consuming approach to the analysis of this initial research. As interviews are used throughout security science to gather data, it will be possible to transfer the methodology developed here to other areas.
