Using technologies to support investigative interviewers in detecting deception

Lead Research Organisation: University of Sussex
Department Name: Sch of Engineering and Informatics

Abstract

The project explores how investigative interviews (e.g., police, immigration, HMRC, benefits, etc.) can be facilitated by the provision of technological support. This support takes the form of a user interface that displays factoids relevant to the current stage of the interview, for example the name of a person the interviewee should know. These factoids are extracted from knowledge bases such as Wikipedia and also from the Web sites of relevant organisations. This Web Information Extraction is the key topic of this research. The challenge is to perform Named Entity Recognition and Co-reference Resolution on a whole Web site, taking into account the richer information present on the Web, such as formatting, position, titles and headings. These extracted entities for each Web page are then integrated to form an entity graph for the whole Web site that can be consumed by the user interface. A semi-supervised approach to training direct on HTML is proposed, guided by a lexicon extracted from Wikipedia.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/N509784/1 01/10/2016 30/09/2021
1955087 Studentship EP/N509784/1 01/03/2016 28/02/2021 Colin Ashby
 
Description This thesis presents the design, implementation and evaluation of an application designed to support interviewers in detecting deception. This application is evaluated in a job interviewing study using novice interviewers, which shows it to be a highly effective method of deception detection, correctly identifying 68.8% of deceivers overall, an increase of 107% and 97% over two baselines without application support, while also reducing false positives.
Exploitation Route Deception detection researchers may be interested in our approach which enabled novice interviewers without specialised contextual knowledge to achieve a good deception detection result through the use of our supporting application Intek.
Sectors Digital/Communication/Information Technologies (including Software),Financial Services, and Management Consultancy,Security and Diplomacy

 
Title Deeper Web Entity Dataset 
Description A dataset based on DBpedia Org/Person tuples, that labels mentions of Persons from said Orgs website up to a depth of 3 pages. Various heuristic techniques are used to reduce false negatives. 
Type Of Material Database/Collection of data 
Year Produced 2019 
Provided To Others? No  
Impact This dataset demonstrates the positive impact on F1 score, of the inclusion of HTML tag types, in real-world Named Entity Recognition. 
 
Title Web Entity Dataset 
Description A summarised collection of Web data that identifies Named Entities in the word/tag sequences. 
Type Of Material Database/Collection of data 
Year Produced 2018 
Provided To Others? No  
Impact Enables the testing of the one of the main hypotheses of this research. 
 
Title Interview assistive user interface 
Description The system suggests deeper lines of questioning to an interviewer in real-time, based on initial snippets of information e.g. home address. 
Type Of Technology Webtool/Application 
Year Produced 2017 
Impact It has played a part in driving the development of the associated theoretical work in Detecting Deception by my colleagues in Psychology. 
 
Title Webtool/Application - Interview assistive user interface v2 
Description A significant update to the initial Interview Assistance app based on scenario-based interview transcripts, user input and expert input. Breadth and depth of Topics, as well as Topic accuracy have been improved. Speech interface has been rationalised. 
Type Of Technology Webtool/Application 
Year Produced 2020 
Impact It will be used to design a trial to assess the effectiveness of interview assistance, especially with regard to lesser experiences interviewers. 
 
Description Sussex Impact Day 2018 
Form Of Engagement Activity A talk or presentation
Part Of Official Scheme? No
Geographic Reach Regional
Primary Audience Industry/Business
Results and Impact Sussex Research Impact Day was an event featuring several speakers and presentations from University of Sussex to industry and academia with the aim of demonstrating the applications of our research. My input was a demonstration of the system I've been working on to various interested parties.
Year(s) Of Engagement Activity 2018
URL https://www.sutori.com/story/sussex-impact-day-2018--DD34TpGt6ETTpQonTE9M1m4N