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Articles 1 - 5 of 5
Full-Text Articles in Computational Linguistics
Context And Coherence, By Una Stojnic, Robert Stainton, Arthur Sullivan
Context And Coherence, By Una Stojnic, Robert Stainton, Arthur Sullivan
Philosophy Publications
No abstract provided.
Applying Positive Psychology’S Subjective Well-Being To Online Interactions, Nicole Delellis, Dominique Kelly, Liu Yifan, Alex Mayhew, Yimin Chen, Victoria Rubin, Sarah Cornwell
Applying Positive Psychology’S Subjective Well-Being To Online Interactions, Nicole Delellis, Dominique Kelly, Liu Yifan, Alex Mayhew, Yimin Chen, Victoria Rubin, Sarah Cornwell
Data and Test Instruments
This paper outlines the complexity of the psychological construct of individuals' subjective well-being (SWB) and argues for the importance of examining behaviours and linguistic expression of individuals online social interactions in relation to self-reported SWB. This paper calls for a systematic review of the psychology research which examines SWB and its association with various character strengths, personality traits, and behaviours. While the Big Five personality traits (OCEAN) have an underlying neuropsychological basis and are considered as universal dimensions of personality along which humans differ one from another, minimal research has attempted to evaluate the relationship between personality traits, SWB, and …
Misinformation And Disinformation: Detecting Fakes With The Eye And Ai, Victoria Rubin
Misinformation And Disinformation: Detecting Fakes With The Eye And Ai, Victoria Rubin
Data and Test Instruments
How do we detect, deter, and prevent the spread of mis- and disinformationwith the human eye and AI? How does theory inform the practice, and how do theevidence-based research and best practices in lie-catching and truth-seekingprofessions—inform AI? The book looks into well-established human practicessuch as the routines and processes used in detective work, journalism, and scientificinquiry, and how they contribute toward innovative AI solutions. The book explainsthe principles, inner workings, and recent evolution of five types of state-of-the-artAI technologies suitable for curtailing the spread of mis- and disinformation:automated deception detectors, clickbait detectors, satirical fake detectors, rumordebunkers, and computational fact-checking tools.
Detecting Clickbait: Here’S How To Do It, Christopher Brogly, Victoria Rubin
Detecting Clickbait: Here’S How To Do It, Christopher Brogly, Victoria Rubin
Data and Test Instruments
Automatic clickbait detection is a relatively novel task in natural language processing (NLP) and machine learning (ML). “Clickbait” is a hyperlink created primarily to attract attention to its target content. This article introduces a binary classifier, the Language and Information Technology Research Lab (LiT.RL, pronounced “literal”) Clickbait Detector, which automatically distinguishes clickbait from nonclickbait. We used NLP and ML for 38 textual features, contrasting clickbait with “headlinese.” When tested on 11,000 hyperlinks, it achieves 94 per cent accuracy using a support vector machine. Integrated with the LiT.RL News Verification Browser, a downloadable stand-alone research tool, the Clickbait Detector user interface …
Towards News Verification: Deception Detection Methods For News Discourse, Yimin Chen, Victoria L. Rubin, Niall Conroy
Towards News Verification: Deception Detection Methods For News Discourse, Yimin Chen, Victoria L. Rubin, Niall Conroy
FIMS Presentations
News verification is a process of determining whether a particular news report is truthful or deceptive. Deliberately deceptive (fabricated) news creates false conclusions in the readers’ minds. Truthful (authentic) news matches the writer’s knowledge. How do you tell the difference between the two in an automated way? To investigate this question, we analyzed rhetorical structures, discourse constituent parts and their coherence relations in deceptive and truthful news sample from NPR’s “Bluff the Listener”. Subsequently, we applied a vector space model to cluster the news by discourse feature similarity, achieving 63% accuracy. Our predictive model is not significantly better than chance …