Neuroscience research articles are provided.
What is neuroscience? Neuroscience is the scientific study of nervous systems. Neuroscience can involve research from many branches of science including those involving neurology, brain science, neurobiology, psychology, computer science, artificial intelligence, statistics, prosthetics, neuroimaging, engineering, medicine, physics, mathematics, pharmacology, electrophysiology, biology, robotics and technology.
– These articles focus mainly on neurology research. – What is neurology? – Definition of neurology: a science involved in the study of the nervous systems, especially of the diseases and disorders affecting them. – Neurology research can include information involving brain research, neurological disorders, medicine, brain cancer, peripheral nervous systems, central nervous systems, nerve damage, brain tumors, seizures, neurosurgery, electrophysiology, BMI, brain injuries, paralysis and spinal cord treatments.
What is Psychology? Definition of Psychology: Psychology is the study of behavior in an individual, or group. Psychology news articles are listed below.
Artificial Intelligence articles involve programming, neural engineering, artificial neural networks, artificial life, a-life, floyds, boids, emergence, machine learning, neuralbots, neuralrobotics, computational neuroscience and more involving A.I. research.
Robotics articles will cover robotics research press releases. Robotics news from universities, labs, researchers, engineers, students, high schools, conventions, competitions and more are posted and welcome.
Genetics articles related to neuroscience research will be listed here.
Neurotechnology research articles deal with robotics, AI, deep learning, machine learning, Brain Computer Interfaces, neuroprosthetics, neural implants and more. Read the latest neurotech news articles below.
Summary: A machine learning classifier identified, with over 65% accuracy, April Fools hoaxes and fake news stories. Based on the findings, researchers present guidelines for recognizing April Fools hoaxes and fake news stories in the media.
Source: Lancaster University
Studying April Fools hoax news stories could offer clues to spotting ‘fake news’ articles, new research reveals.
Academic experts in Natural Language Processing from Lancaster University who are interested in deception have compared the language used within written April Fools hoaxes and fake news stories.
They have discovered that there are similarities in the written structure of humorous April Fools hoaxes – the spoof articles published by media outlets every April 1st – and malicious fake news stories.
The researchers have compiled a novel dataset, or corpus, of more than 500 April Fools articles sourced from more than 370 websites and written over 14 years.
“April Fools hoaxes are very useful because they provide us with a verifiable body of deceptive texts that give us an opportunity to find out about the linguistic techniques used when an author writes something fictitious disguised as a factual account,” said Edward Dearden from Lancaster University, and lead author of the research. “By looking at the language used in April Fools and comparing them with fake news stories we can get a better picture of the kinds of language used by authors of disinformation.”
A comparison of April Fools hoax texts against genuine news articles written in the same period – but not published on April 1st – revealed stylistic differences.
Researchers focused on specific features within the texts, such as the number of details used, vagueness, formality of writing style and complexity of language.
They then compared the April Fools stories with a ‘fake news’ dataset, previously compiled by a different team of researchers.
Although not all of the features found in April Fools hoaxes were found to be useful for detecting fake news, there were a number of similar characteristics found across both.
They found April Fools hoaxes and fake news articles tend to contain less complex language, an easier reading difficulty, and longer sentences than genuine news.
Important details for news stories, such as names, places, dates and times, were found to be used less frequently within April Fools hoaxes and fake news. However, proper nouns, such as the names of prominent politicians ‘Trump’ or ‘Hillary’, are more abundant in fake news than in genuine news articles or April Fools, which have significantly fewer.
First person pronouns, such as ‘we’, are also a prominent feature for both April Fools and fake news. This goes against traditional thinking in deception detection, which suggests liars use fewer first-person pronouns.
The researchers found that April fools hoax stories, when compared to genuine news:
Fake news stories, when compared to genuine news:
The researchers also created a machine learning ‘classifier’ to identify if articles are April Fools hoaxes, fake news or genuine news stories. The classifier achieved a 75 percent accuracy at identifying April Fools articles and 72 percent for identifying fake news stories. When the classifier was trained on April Fools hoaxes and set the task of identifying fake news it recorded an accuracy of more than 65 percent.
Dr. Alistair Baron, the co-author of the paper, said: “Looking at details and complexities within a text are crucial when trying to determine if an article is a hoax. Although there are many differences, our results suggest that April Fools and fake news articles share some similar features, mostly involving structural complexity.
“Our findings suggest that there are certain features in common between different forms of disinformation and exploring these similarities may provide important insights for future research into deceptive news stories.”
The research has been outlined in the paper ‘Fool’s Errand: Looking at April Fools Hoaxes as Disinformation through the Lens of Deception and Humour’, which will be presented at the 20th International Conference on Computational Linguistics and Intelligent Text Processing, to be held in La Rochelle in April.
Funding: The paper’s authors are Edward Dearden and Alistair Baron of Lancaster University. Edward Dearden’s Ph.D. studies have been supported by the Engineering and Physical Sciences Research Council.
[divider]About this neuroscience research article[/divider]
Source: Lancaster University Media Contacts: Gina DiGravio – Lancaster University Image Source: The image is in the public domain.
Original Research: The findings will be presented at the 20th International Conference on Computational Linguistics and Intelligent Text Processing in La Rochelle, France.
[divider]Feel free to share this Neuroscience News.[/divider]