Rob N Procter

The University of Warwick · Department of Computer Science

The sheer number of research outputs published every year makes systematic reviewing increasingly time- and resource-intensive. This paper explores the use of machine learning techniques to help navigate the systematic review process. ML has previously been used to reliably 'screen' articles for review - that is, identify relevant articles based on...

To seek reliable information sources for news events, we introduce a novel task of expert recommendation, which aims to identify trustworthy sources based on their previously quoted statements. To achieve this, we built a novel dataset, called NewsQuote, consisting of 23,571 quote-speaker pairs sourced from a collection of news articles. We formula...

In this paper we present an ethnographic study of the work of histopathologists as they grapple with the twin innovations of transitioning to digital biopsy images and the prospective adoption of an AI-based clinical decision support system (CDSS). We explore how they are adapting to the former and their expectations of the latter. The study’s ethn...

Most existing topic models still require bag-of-words (BoW) information. This limits their ability to capture word order information and causes them to suffer from the out-of-vocabulary (OOV) issue, i.e. they cannot handle unobserved words in new documents. Contextualized word embeddings show superiority in word sense disambiguation and prove to be...

The objective of this research is to determine the potential of scope 3 supply chain emissions generated by end user computers within the United Kingdom government and to test current scope 2 calculation methods to improve annual reporting procedures. The supply chain analysis is accomplished by using existing asset profile data to determine the nu...

The purpose of this research is to generate findings to support the reduction of computer supply chain greenhouse gas emissions. This is achieved by answering the question, 'can greenhouse gas abatement be delivered by alternative computer operating system displacement strategies?' We hypothesised that extending the useful lifespan of end user comp...

Background Informal carers play a major role in supporting relatives and friends who are sick, disabled, or frail. Access to information, guidance, and support that are relevant to the lives and circumstances of carers is critical to carers feeling supported in their role. When unmet, this need is known to adversely affect carer resilience and well...

Objective Physical access to food may affect diet and thus obesity rates. We build upon existing work to better understand how socio-economic characteristics of locations are associated with childhood overweight. Design Using cross-sectional design and publicly available data, the study specifically compares rural and urban areas, including intera...

To enhance the ability to find credible evidence in news articles, we propose a novel task of expert recommendation, which aims to identify trustworthy experts on a specific news topic. To achieve the aim, we describe the construction of a novel NewsQuote dataset consisting of 24,031 quote-speaker pairs that appeared on a COVID-19 news corpus. We d...

Social media and user-generated content (UGC) have become increasingly important features of journalistic work in a number of different ways. However, the growth of misinformation means that news organisations have had devote more and more resources to determining its veracity and to publishing corrections if it is found to be misleading. In this w...

Human-in-the-loop topic modelling incorporates users' knowledge into the modelling process, enabling them to refine the model iteratively. Recent research has demonstrated the value of user feedback, but there are still issues to consider, such as the difficulty in tracking changes, comparing different models and the lack of evaluation based on rea...

In this paper we report on ethnographic fieldwork of the work of cellular pathologists as they grapple with the twin innovations of transitioning to digital biopsy images and the prospects for the adoption of clinical decision support systems (CDSS). We explore how they are adapting to the former and their expectations of the latter. We use this ca...

In this demo, we introduce a web-based misinformation detection system PANACEA on COVID-19 related claims, which has two modules, fact-checking and rumour detection. Our fact-checking module, which is supported by novel natural language inference methods with a self-attention network, outperforms state-of-the-art approaches. It is also able to give...

Research on automated social media rumour verification, the task of identifying the veracity of questionable information circulating on social media, has yielded neural models achieving high performance, with accuracy scores that often exceed 90%. However, none of these studies focus on the real-world generalisability of the proposed approaches, th...

BACKGROUND The rapid implementation of telemedicine during the early stages of the COVID-19 pandemic raises questions about impacts and sustainability of this intervention at global level. OBJECTIVE Identify immediate experiences and impacts on patients and clinicians across the globe of this transformation, focusing on: Patient Experience, Clinic...

The need for AI systems to provide explanations for their behaviour is now widely recognised as key to their adoption. In this paper, we examine the problem of trustworthy AI and explore what delivering this means in practice, with a focus on healthcare applications. Work in this area typically treats trustworthy AI as a problem of Human-Computer I...

Question Answering (QA) is a growing area of research, often used to facilitate the extraction of information from within documents. State-of-the-art QA models are usually pre-trained on domain-general corpora like Wikipedia and thus tend to struggle on out-of-domain documents without fine-tuning. We demonstrate that synthetic domain-specific datas...

The need for AI systems to provide explanations for their behaviour is now widely recognised as key to their adoption. In this paper, we examine the problem of trustworthy AI and explore what delivering this means in practice, with a focus on healthcare applications. Work in this area typically treats trustworthy AI as a problem of Human-Computer I...

Opinion summarisation synthesises opinions expressed in a group of documents discussing the same topic to produce a single summary. Recent work has looked at opinion summarisation of clusters of social media posts. Such posts are noisy and have unpredictable structure, posing additional challenges for the construction of the summary distribution an...

We introduce the task of microblog opinion summarization (MOS) and share a dataset of 3100 gold-standard opinion summaries to facilitate research in this domain. The dataset contains summaries of tweets spanning a 2-year period and covers more topics than any other public Twitter summarization dataset. Summaries are abstractive in nature and have b...

The challenging task of embedding innovative participatory processes and technologies within local government often falls upon local council officers. Using qualitative data collection and analysis, we investigate the ongoing work of Scottish local councils seeking to run the process of participatory budgeting (PB) within their institution, the use...

In this article, we investigate the privacy and security challenges of the smart home as perceived by the industry, with findings relating to cybersecurity awareness, transparency on legal data use, malicious data use, regulation issues, liability, and market incentives for cybersecurity; we also reveal how the industry has been responding to these...

Today’s conflicts are becoming increasingly complex, fluid, and fragmented, often involving a host of national and international actors with multiple and often divergent interests. This development poses significant challenges for conflict mediation, as mediators struggle to make sense of conflict dynamics, such as the range of conflict parties and...

We introduce the task of microblog opinion summarisation (MOS) and share a dataset of 3100 gold-standard opinion summaries to facilitate research in this domain. The dataset contains summaries of tweets spanning a 2-year period and covers more topics than any other public Twitter summarisation dataset. Summaries are abstractive in nature and have b...

BACKGROUND Informal carers make a substantial contribution to health and social care, providing care and support to growing numbers of sick, disabled or frail relatives and friends. The importance of carers having access to relevant information, guidance and support that is adaptive to changing needs and circumstances is well recognised. However, m...

Today's conflicts are becoming increasingly complex, fluid and fragmented, often involving a host of national and international actors with multiple and often divergent interests. This development poses significant challenges for conflict mediation, as mediators struggle to make sense of conflict dynamics, such as the range of conflict parties and...

Background Before the declaration of the COVID-19 pandemic in March 2020, primary care in most countries relied on face-to-face consultations, with relatively limited use of telemedicine. Lockdowns and social distancing measures during the early stages of the pandemic led to rapid, widely spread telemedicine adoption in healthcare settings. The rap...

In this paper we consider some empirical materials from our ongoing research into forms of everyday detection and diagnosis work in healthcare settings, and how these relate to issues of trust; trust in people, in technology, processes and in data.

Building models to detect vaccine attitudes on social media is challenging because of the composite, often intricate aspects involved, and the limited availability of annotated data. Existing approaches have relied heavily on supervised training that requires abundant annotations and pre-defined aspect categories. Instead, with the aim of leveragin...

We present a comprehensive work on automated veracity assessment from dataset creation to developing novel methods based on Natural Language Inference (NLI), focusing on misinformation related to the COVID-19 pandemic. We first describe the construction of the novel PANACEA dataset consisting of heterogeneous claims on COVID-19 and their respective...

The introduction of online marketplace platforms has led to the advent of new forms of flexible, on-demand (or 'gig') work. Yet, most prior research concerning the experience of gig workers examines delivery or crowdsourcing platforms, while the experience of the large numbers of workers who undertake educational labour in the form of tutoring gigs...

In recent years participatory budgeting (PB) in Scotland has grown from a handful of community-led processes to a movement supported by local and national government. This is epitomized by an agreement between the Scottish Government and the Convention of Scottish Local Authorities (COSLA) that at least 1% of local authority budgets will be subject...

We present work on summarising deliberative processes for non-English languages. Unlike commonly studied datasets, such as news articles , this deliberation dataset reflects difficulties of combining multiple narratives, mostly of poor grammatical quality, in a single text. We report an extensive evaluation of a wide range of abstractive summarisat...

We present work on summarising deliberative processes for non-English languages. Unlike commonly studied datasets, such as news articles, this deliberation dataset reflects difficulties of combining multiple narratives, mostly of poor grammatical quality, in a single text. We report an extensive evaluation of a wide range of abstractive summarisati...

Participatory budgeting (PB) is already well established in Scotland in the form of community led grant-making yet has recently transformed from a grass-roots activity to a mainstream process or embedded 'policy instrument'. An integral part of this turn is the use of the Consul digital platform as the primary means of citizen participation. Using...

Background: Existing research suggests that physical access to food can affect diet quality and thus obesity rates. When defining retail food environment (RFE) quantitatively, there is a little agreement on how to measure "lack of healthy food" and what parameters to use, resulting in a heterogeneity of study designs and outcome measures. In turn,...

Today's conflicts are becoming increasingly complex, fluid and fragmented, often involving a host of national and international actors with multiple and often divergent interests. This development poses significant challenges for conflict mediation, as mediators struggle to make sense of conflict dynamics, such as the range of conflict parties and...

This paper presents a unique study into how to identify a meso-level normative (i.e., institutional) hierarchy of procedures that aim to deliver the ecological status of waterbodies in the UK. Using traditional survey and workshop methods, the majority of recent studies concentrate on engagement practices between macro- (government bodies) and micr...

The development of democratic systems is a crucial task as confirmed by its selection as one of the Millennium Sustainable Development Goals by the United Nations. In this article, we report on the progress of a project that aims to address barriers, one of which is information overload, to achieving effective direct citizen participation in democr...

Collecting together microblogs representing opinions about the same topics within the same timeframe is useful to a number of different tasks and practitioners. A major question is how to evaluate the quality of such thematic clusters. Here we create a corpus of microblog clusters from three different domains and time windows and define the task of...

Topic modeling is an unsupervised method for revealing the hidden semantic structure of a corpus. It has been increasingly widely adopted as a tool in the social sciences, including political science, digital humanities and sociological research in general. One desirable property of topic models is to allow users to find topics describing a specifi...

Background: Before the declaration of the COVID-19 pandemic in March 2020, primary care relied on face-to-face consultations, with relatively limited use of telemedicine. The rapid uptake that occurred following the onset of the pandemic in countries such as the United Kingdom, Canada and New Zealand prompts questions around the drivers and extent...

The development of democratic systems is a crucial task as confirmed by its selection as one of the Millennium Sustainable Development Goals by the United Nations. In this article, we report on the progress of a project that aims to address barriers, one of which is information overload, to achieving effective direct citizen participation in democr...

Semantic drift is a well-known concept in distributional semantics, which is used to demonstrate gradual, long-term changes in meanings and sentiments of words and is largely detectable by studying the composition of large corpora. In our previous work, which used ontological relationships between words and phrases, we established that certain kind...

Topic modeling is an unsupervised method for revealing the hidden semantic structure of a corpus. It has been increasingly widely adopted as a tool in the social sciences, including political science, digital humanities and sociological research in general. One desirable property of topic models is to allow users to find topics describing a specifi...

Social media exhibits the core characteristics of emergent technologies. It is disruptive of established ways of organising social relations, is evolving at an exponential pace and its effects, including the production of new ‘goods’ and ‘bads’, are highly uncertain. Interest in understanding these effects has intensified in the context of fears ov...

We examine the problem of explainable AI (xAI) and explore what delivering xAI means in practice, particularly in contexts that involve formal or informal and ad-hoc collaboration where agency and accountability in decision-making are achieved and sustained interactionally. We use an example from an earlier study of collaborative decision-making in...

Trust and confidence in democratic institutions is at an all-time low. At the same time, many of the complex issues faced by city administrators and politicians remain unresolved. To tackle these concerns, many argue that citizens should, through the use of digital platforms, have greater involvement in decision-making processes. This paper describ...

Executive Summary There is a growing consensus that we are at the start of a fourth industrial revolution, driven by developments in Artificial Intelligence, machine learning, robotics, the Internet of Things, 3-D printing, nanotechnology, biotechnology, 5G, new forms of energy storage and quantum computing. This wave of technical innovations is al...

As breaking news unfolds, social media has become the go-to platform to learn about the latest updates from journalists and eyewitnesses on the ground. The fact that anybody can post content in social media during these breaking news leads to posting and diffusion of unverified rumours, which in turn produces uncertainty and increases anxiety. Give...

Businesses in the smart home sector are actively promoting the benefits of smart home technologies for consumers, such as convenience, economy and home security. To better understand meanings of and trust in the smart home, we carried out a nationally representative survey of UK consumers designed to measure adoption and acceptability, focusing on...

On 2 May 2019, during the UK local elections, an e-voting trial was conducted in Gateshead, using a touch-screen end-to-end verifiable e-voting system. This was the first trial of verifiable e-voting for polling station voting in the UK, and it presented a case study to envisage the future of e-voting.

Mobile wireless networks underpin digital economies and smart cities. Local and national scale network failures cause widespread social and economic impact. Self-reporting of consumer experience on social media platforms can inform operators. This paper investigates an innovative method to detect the consumer experience to outage events in both tem...

This paper explores ways in which the harmful effects of cyber hate may be mitigated through mechanisms for enhancing the self governance of new digital spaces. We report findings from a mixed methods study of responses to cyber hate posts, which aimed to: (i) understand how people interact in this context by undertaking qualitative interaction ana...

Hyper-dense wireless network deployment is one of the popular solutions to meeting high capacity requirement for 5G delivery. However, current operator understanding of consumer satisfaction comes from call centres and base station quality-of-service (QoS) reports with poor geographic accuracy. The dramatic increase in geo-tagged social media posts...

The Internet of Things (or IoT), which enables the networked interconnection of everyday objects, is becoming increasingly popular in many aspects of our lives ranging from entertainment to health care. While the IoT brings a set of invaluable advantages and opportunities with it, there is also evidence of numerous challenges that are yet to be res...

The Internet of Things (or IoT), which enables the networked interconnection of everyday objects, is becoming increasingly popular in many aspects of our lives ranging from entertainment to health care. While the IoT brings a set of invaluable advantages and opportunities with it, there is also evidence of numerous challenges that are yet to be res...

Electronic tracking through global positioning systems (GPSs) is used to monitor people with cognitive impairment who “wander” outside the home. This ethnographic study explored how GPS-monitored wandering was experienced by individuals, lay carers, and professional staff. Seven in-depth case studies revealed that wandering was often an enjoyable a...

Upon publication of the original article [1], Gregory Maniatopoulos' name was incorrectly given as 'Greg Maniatopoulous'. This has now been corrected in the original article.

Cambridge Core - General - Managing Research Data - edited by Graham Pryor

Background: Failures and partial successes are common in technology-supported innovation programmes in health and social care. Complexity theory can help explain why. Phenomena may be simple (straightforward, predictable, few components), complicated (multiple interacting components or issues) or complex (dynamic, unpredictable, not easily disaggr...

Background: Accelerating the implementation of new technology in healthcare is typically complex and multi-faceted. One strategy is to charge a national agency with the responsibility for facilitating implementation. This study examines the role of such an agency in the English National Health Service. In particular, it compares two different faci...

Assisted living technologies may help people live independently while also—potentially—reducing health and care costs. But they are notoriously difficult to implement at scale and many devices are abandoned following initial adoption. We report findings from a study of global positioning system (GPS) tracking devices intended to support the indepen...

Despite the increasing use of social media platforms for information and news gathering, its unmoderated nature often leads to the emergence and spread of rumours, i.e. pieces of information that are unverified at the time of posting. At the same time, the openness of social media platforms provides opportunities to study how users share and discus...

The increasing popularity of social media platforms creates new digital social networks in which individuals can interact and share information, news, and opinion. The use of these technologies appears to have the capacity to transform current social configurations and relations, not least within the public and civic spheres. Within the social scie...

Social media and data mining are increasingly being used to analyse political and societal issues. Here we undertake the classification of social media users as supporting or opposing ongoing independence movements in their territories. Independence movements occur in territories whose citizens have conflicting national identities; users with oppos...

Rumour stance classification, defined as classifying the stance of specific social media posts into one of supporting, denying, querying or commenting on an earlier post, is becoming of increasing interest to researchers. While most previous work has focused on using individual tweets as classifier inputs, here we report on the performance of seque...

Background Many promising technological innovations in health and social care are characterized by nonadoption or abandonment by individuals or by failed attempts to scale up locally, spread distantly, or sustain the innovation long term at the organization or system level. Objective Our objective was to produce an evidence-based, theory-informed,...

We present a system for time-sensitive, topic-based summarisation of sentiment around target entities and topics in collections of tweets. We describe the main elements of the system and present two examples of sentiment analysis of topics related to the 2017 UK general election.

Recent years have seen a remarkable proliferation of studies attempting to establish relationships between observable online human behaviour and various types of crisis (social, political, economic and natural). Methods utilizing user generated content (UGC) have been already applied to various environmental hazards, such as floods, wildfires, eart...

Tools that are able to detect unverified information posted on social media during a news event can help to avoid the spread of rumours that turn out to be false. In this paper we compare a novel approach using Conditional Random Fields that learns from the sequential dynamics of social media posts with the current state-of-the-art rumour detection...