Search Results for author: Rob Procter

Found 34 papers, 7 papers with code

Generating Zero-shot Abstractive Explanations for Rumour Verification

1 code implementation23 Jan 2024 Iman Munire Bilal, Preslav Nakov, Rob Procter, Maria Liakata

The task of rumour verification in social media concerns assessing the veracity of a claim on the basis of conversation threads that result from it.

Few-Shot Learning Informativeness +2

CWTM: Leveraging Contextualized Word Embeddings from BERT for Neural Topic Modeling

1 code implementation16 May 2023 Zheng Fang, Yulan He, Rob Procter

Most existing topic models rely on bag-of-words (BOW) representation, which limits their ability to capture word order information and leads to challenges with out-of-vocabulary (OOV) words in new documents.

Document Classification Language Modelling +5

NewsQuote: A Dataset Built on Quote Extraction and Attribution for Expert Recommendation in Fact-Checking

1 code implementation5 May 2023 Wenjia Zhang, Lin Gui, Rob Procter, Yulan He

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.

Fact Checking Question Answering +1

A User-Centered, Interactive, Human-in-the-Loop Topic Modelling System

no code implementations4 Apr 2023 Zheng Fang, Lama Alqazlan, Du Liu, Yulan He, Rob Procter

Human-in-the-loop topic modelling incorporates users' knowledge into the modelling process, enabling them to refine the model iteratively.

Topic Models

PANACEA: An Automated Misinformation Detection System on COVID-19

no code implementations28 Feb 2023 Runcong Zhao, Miguel Arana-Catania, Lixing Zhu, Elena Kochkina, Lin Gui, Arkaitz Zubiaga, Rob Procter, Maria Liakata, Yulan He

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.

Fact Checking Misinformation +2

A Pipeline for Generating, Annotating and Employing Synthetic Data for Real World Question Answering

1 code implementation30 Nov 2022 Matthew Maufe, James Ravenscroft, Rob Procter, Maria Liakata

Question Answering (QA) is a growing area of research, often used to facilitate the extraction of information from within documents.

Question Answering

Holding AI to Account: Challenges for the Delivery of Trustworthy AI in Healthcare

no code implementations29 Nov 2022 Rob Procter, Peter Tolmie, Mark Rouncefield

We use these findings to enrich existing understandings of the requirements for trustworthy AI and to outline some candidate solutions to the problems of making AI accountable both to individual users and organisationally.

Unsupervised Opinion Summarisation in the Wasserstein Space

no code implementations27 Nov 2022 Jiayu Song, Iman Munire Bilal, Adam Tsakalidis, Rob Procter, Maria Liakata

A Variational Autoencoder is used to get the distribution of documents/posts, and the distributions are disentangled into separate semantic and syntactic spaces.

Abstractive Text Summarization

Template-based Abstractive Microblog Opinion Summarisation

no code implementations8 Aug 2022 Iman Munire Bilal, Bo wang, Adam Tsakalidis, Dong Nguyen, Rob Procter, Maria Liakata

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.

Supporting peace negotiations in the Yemen war through machine learning

no code implementations23 Jul 2022 M. Arana-Catania, F. A. Van Lier, Rob Procter

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 the evolution of their political positions, the distinction between relevant and less relevant actors in peace-making, or the identification of key conflict issues and their interdependence.

BIG-bench Machine Learning Management

Disentangled Learning of Stance and Aspect Topics for Vaccine Attitude Detection in Social Media

1 code implementation NAACL 2022 Lixing Zhu, Zheng Fang, Gabriele Pergola, Rob Procter, Yulan He

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.

Aspect-Based Sentiment Analysis Aspect-Based Sentiment Analysis (ABSA) +1

Using Computational Grounded Theory to Understand Tutors' Experiences in the Gig Economy

no code implementations24 Jan 2022 Lama Alqazlan, Rob Procter, Michael Castelle

To address this, we use a computational grounded theory approach to analyse tutors' discussions on Reddit.

Evaluating the application of NLP tools in mainstream participatory budgeting processes in Scotland

no code implementations23 Nov 2021 Jonathan Davies, Miguel Arana-Catania, Rob Procter, Felix-Anselm van Lier, Yulan He

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.

A mixed-methods ethnographic approach to participatory budgeting in Scotland

no code implementations20 Sep 2021 Jonathan Davies, M. Arana-Catania, Rob Procter, F. A. Van Lier, Yulan He

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'.

Machine Learning for Mediation in Armed Conflicts

no code implementations26 Aug 2021 M. Arana-Catania, F. A. Van Lier, Rob Procter

Apart from illustrating the potential of machine learning tools in conflict mediation, the paper also emphasises the importance of interdisciplinary and participatory research design for the development of context-sensitive and targeted tools and to ensure meaningful and responsible implementation.

BIG-bench Machine Learning

Evaluation of Thematic Coherence in Microblogs

no code implementations ACL 2021 Iman Munire Bilal, Bo wang, Maria Liakata, Rob Procter, Adam Tsakalidis

Here we create a corpus of microblog clusters from three different domains and time windows and define the task of evaluating thematic coherence.

Text Generation

A Query-Driven Topic Model

no code implementations Findings (ACL) 2021 Zheng Fang, Yulan He, Rob Procter

Topic modeling is an unsupervised method for revealing the hidden semantic structure of a corpus.

Topic Models

Citizen Participation and Machine Learning for a Better Democracy

no code implementations28 Feb 2021 M. Arana-Catania, F. A. Van Lier, Rob Procter, Nataliya Tkachenko, Yulan He, Arkaitz Zubiaga, Maria Liakata

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.

BIG-bench Machine Learning Decision Making

Discourse-Aware Rumour Stance Classification in Social Media Using Sequential Classifiers

no code implementations6 Dec 2017 Arkaitz Zubiaga, Elena Kochkina, Maria Liakata, Rob Procter, Michal Lukasik, Kalina Bontcheva, Trevor Cohn, Isabelle Augenstein

We show that sequential classifiers that exploit the use of discourse properties in social media conversations while using only local features, outperform non-sequential classifiers.

General Classification Stance Classification

Detection and Resolution of Rumours in Social Media: A Survey

no code implementations3 Apr 2017 Arkaitz Zubiaga, Ahmet Aker, Kalina Bontcheva, Maria Liakata, Rob Procter

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.

Classification General Classification +3

TDParse: Multi-target-specific sentiment recognition on Twitter

no code implementations EACL 2017 Bo Wang, Maria Liakata, Arkaitz Zubiaga, Rob Procter

Existing target-specific sentiment recognition methods consider only a single target per tweet, and have been shown to miss nearly half of the actual targets mentioned.

Dependency Parsing Opinion Mining +1

Political Homophily in Independence Movements: Analysing and Classifying Social Media Users by National Identity

no code implementations27 Feb 2017 Arkaitz Zubiaga, Bo wang, Maria Liakata, Rob Procter

Independence movements occur in territories whose citizens have conflicting national identities; users with opposing national identities will then support or oppose the sense of being part of an independent nation that differs from the officially recognised country.

General Classification

Learning Reporting Dynamics during Breaking News for Rumour Detection in Social Media

2 code implementations24 Oct 2016 Arkaitz Zubiaga, Maria Liakata, Rob Procter

In this paper we introduce a novel approach to rumour detection that learns from the sequential dynamics of reporting during breaking news in social media to detect rumours in new stories.

Rumour Detection

Stance Classification in Rumours as a Sequential Task Exploiting the Tree Structure of Social Media Conversations

no code implementations COLING 2016 Arkaitz Zubiaga, Elena Kochkina, Maria Liakata, Rob Procter, Michal Lukasik

Rumour stance classification, the task that determines if each tweet in a collection discussing a rumour is supporting, denying, questioning or simply commenting on the rumour, has been attracting substantial interest.

General Classification Rumour Detection +1

Towards Real-Time, Country-Level Location Classification of Worldwide Tweets

1 code implementation25 Apr 2016 Arkaitz Zubiaga, Alex Voss, Rob Procter, Maria Liakata, Bo wang, Adam Tsakalidis

In contrast to much previous work that has focused on location classification of tweets restricted to a specific country, here we undertake the task in a broader context by classifying global tweets at the country level, which is so far unexplored in a real-time scenario.

Classification General Classification

A data and analysis resource for an experiment in text mining a collection of micro-blogs on a political topic.

no code implementations LREC 2012 William Black, Rob Procter, Steven Gray, Sophia Ananiadou

The analysis of a corpus of micro-blogs on the topic of the 2011 UK referendum about the Alternative Vote has been undertaken as a joint activity by text miners and social scientists.

Named Entity Recognition (NER) Sentiment Analysis +1

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