Search Results for author: Mike Thelwall

Found 11 papers, 0 papers with code

Can ChatGPT evaluate research quality?

no code implementations8 Feb 2024 Mike Thelwall

In contrast, the average scores from the 15 iterations produced a statistically significant positive correlation of 0. 509.

Predicting article quality scores with machine learning: The UK Research Excellence Framework

no code implementations11 Dec 2022 Mike Thelwall, Kayvan Kousha, Mahshid Abdoli, Emma Stuart, Meiko Makita, Paul Wilson, Jonathan Levitt, Petr Knoth, Matteo Cancellieri

National research evaluation initiatives and incentive schemes have previously chosen between simplistic quantitative indicators and time-consuming peer review, sometimes supported by bibliometrics.

Active Learning

Artificial intelligence technologies to support research assessment: A review

no code implementations11 Dec 2022 Kayvan Kousha, Mike Thelwall

This includes studies that used machine learning techniques to predict citation counts or quality scores for journal articles or conference papers.

Can REF output quality scores be assigned by AI? Experimental evidence

no code implementations11 Dec 2022 Mike Thelwall, Kayvan Kousha, Mahshid Abdoli, Emma Stuart, Meiko Makita, Paul Wilson, Jonathan Levitt

This document describes strategies for using Artificial Intelligence (AI) to predict some journal article scores in future research assessment exercises.

Pot, kettle: Nonliteral titles aren't (natural) science

no code implementations14 Jun 2020 Mike Thelwall

The expressions found are most common in the social sciences and the humanities.

What Makes You Stressed? Finding Reasons From Tweets

no code implementations WS 2018 Reshmi Gopalakrishna Pillai, Mike Thelwall, Constantin Orasan

Detecting stress from social media gives a non-intrusive and inexpensive alternative to traditional tools such as questionnaires or physiological sensors for monitoring mental state of individuals.

BIG-bench Machine Learning

TensiStrength: Stress and relaxation magnitude detection for social media texts

no code implementations1 Jul 2016 Mike Thelwall

In conclusion, TensiStrength and generic machine learning approaches work well enough to be practical choices for intelligent applications that need to take advantage of stress information, and the decision about which to use depends on the nature of the texts analysed and the purpose of the task.

BIG-bench Machine Learning Sentiment Analysis

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