Search Results for author:
Found 18 papers, 1 papers with code
Embedding Privacy in Computational Social Science and Artificial Intelligence Research
Privacy is a human right.
aedFaCT: Scientific Fact-Checking Made Easier via Semi-Automatic Discovery of Relevant Expert Opinions
In this highly digitised world, fake news is a challenging problem that can cause serious harm to society.
Improving Performance of Automatic Keyword Extraction (AKE) Methods Using PoS-Tagging and Enhanced Semantic-Awareness
Automatic keyword extraction (AKE) has gained more importance with the increasing amount of digital textual data that modern computing systems process.
Perspectives of Non-Expert Users on Cyber Security and Privacy: An Analysis of Online Discussions on Twitter
Our analysis revealed a diverse range of topics discussed by non-expert users across the three years, including VPNs, Wi-Fi, smartphones, laptops, smart home devices, financial security, and security and privacy issues involving different stakeholders.
Are You Robert or RoBERTa? Deceiving Online Authorship Attribution Models Using Neural Text Generators
Given the power of natural language models in generating convincing texts, this paper examines the degree to which these language models can generate texts capable of deceiving online AA models.
A Comparison of Online Hate on Reddit and 4chan: A Case Study of the 2020 US Election
The rapid integration of the Internet into our daily lives has led to many benefits but also to a number of new, wide-spread threats such as online hate, trolling, bullying, and generally aggressive behaviours.
Out of the Shadows: Analyzing Anonymous' Twitter Resurgence during the 2020 Black Lives Matter Protests
These findings show that whilst the group has seen a resurgence during the protests, bot activity may be responsible for exaggerating the extent of this resurgence.
Privacy Concerns in Chatbot Interactions: When to Trust and When to Worry
Our results show that the user concerns focus on deleting personal information and concerns about their data's inappropriate use.
StockBabble: A Conversational Financial Agent to support Stock Market Investors
We introduce StockBabble, a conversational agent designed to support understanding and engagement with the stock market.
The Shadowy Lives of Emojis: An Analysis of a Hacktivist Collective's Use of Emojis on Twitter
Finally, we explore the textual context in which these emojis occur, finding that although similarities exist between the emoji usage of our Anonymous and baseline Twitter datasets, Anonymous users appear to have adopted more specific interpretations of certain emojis.
Behind the Mask: A Computational Study of Anonymous' Presence on Twitter
In this paper we re-examine some key findings reported in previous small-scale qualitative studies of the group using a large-scale computational analysis of Anonymous' presence on Twitter.
Is your chatbot GDPR compliant? Open issues in agent design
Conversational agents open the world to new opportunities for human interaction and ubiquitous engagement.
Catching the Phish: Detecting Phishing Attacks using Recurrent Neural Networks (RNNs)
The emergence of online services in our daily lives has been accompanied by a range of malicious attempts to trick individuals into performing undesired actions, often to the benefit of the adversary.
Understanding the Radical Mind: Identifying Signals to Detect Extremist Content on Twitter
We identify several signals, including textual, psychological and behavioural, that together allow for the classification of radical messages.
A semi-supervised approach to message stance classification
Social media communications are becoming increasingly prevalent; some useful, some false, whether unwittingly or maliciously.
A Storm in an IoT Cup: The Emergence of Cyber-Physical Social Machines
The concept of social machines is increasingly being used to characterise various socio-cognitive spaces on the Web.
Using semantic clustering to support situation awareness on Twitter: The case of World Views
The novelty and value of SVOSSTC is its emphasis on utilising the Subject-Verb-Object (SVO) typology in order to construct semantically consistent world views, in which individuals---particularly those involved in crisis response---might achieve an enhanced picture of a situation from social media data.
Determining the Veracity of Rumours on Twitter
For our work, we collected about 100 million public tweets, including users' past tweets, from which we identified 72 rumours (41 true, 31 false).
