R
Rob Procter
Researcher at University of Warwick
Publications - 344
Citations - 11903
Rob Procter is an academic researcher from University of Warwick. The author has contributed to research in topics: Social media & Context (language use). The author has an hindex of 48, co-authored 327 publications receiving 10111 citations. Previous affiliations of Rob Procter include Western General Hospital & University of Edinburgh.
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Journal ArticleDOI
The impact of eHealth on the quality and safety of health care: a systematic overview.
Ashly D. Black,Josip Car,Claudia Pagliari,Chantelle Anandan,Kathrin Cresswell,Tomislav Bokun,Brian McKinstry,Rob Procter,Azeem Majeed,Aziz Sheikh +9 more
TL;DR: The findings of their systematic overview that assessed the impact of eHealth solutions on the quality and safety of health care are reported.
Journal ArticleDOI
Beyond Adoption: A New Framework for Theorizing and Evaluating Nonadoption, Abandonment, and Challenges to the Scale-Up, Spread, and Sustainability of Health and Care Technologies
Trisha Greenhalgh,Joseph Wherton,Chrysanthi Papoutsi,Jennifer Lynch,Gemma Hughes,Christine A'Court,Susan Hinder,Nick Fahy,Rob Procter,Sara Shaw +9 more
TL;DR: An evidence-based, theory-informed, and pragmatic framework to help predict and evaluate the success of a technology-supported health or social care program, which has several potential uses and could be applied across a range of technological innovations in health and social care.
Journal ArticleDOI
Analysing how people orient to and spread rumours in social media by looking at conversational threads
TL;DR: The study shows that rumours that are ultimately proven true tend to be resolved faster than those that turn out to be false, and reinforces the need for developing robust machine learning techniques that can provide assistance in real time for assessing the veracity of rumours.
Journal ArticleDOI
Detection and Resolution of Rumours in Social Media: A Survey
TL;DR: The authors provide an overview of research into social media rumours with the ultimate goal of developing a rumour classification system that consists of four components: rumour detection, rumor tracking, rumour stance classification, and rumour veracity classification.
Proceedings ArticleDOI
SemEval-2017 Task 8: RumourEval: Determining rumour veracity and support for rumours
Leon Derczynski,Kalina Bontcheva,Maria Liakata,Rob Procter,Geraldine Wong Sak Hoi,Arkaitz Zubiaga +5 more
TL;DR: An annotation scheme is presented, a large dataset covering multiple topics – each having their own families of claims and replies – and these are used to pose two concrete challenges as well as the results achieved by participants on these challenges.