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Amir Abdul Reda; Semuhi Sinanoglu; Mohamed Abdalla – Sociological Methods & Research, 2024
How can we measure the resource mobilization (RM) efforts of social movements on Twitter? In this article, we create the first ever measure of social movements' RM efforts on a social media platform. To this aim, we create a four-conditional lexicon that can parse through tweets and identify those concerned with RM. We also create a simple RM…
Descriptors: Social Media, Social Action, Natural Language Processing, Politics
Rebeckah K. Fussell; Emily M. Stump; N. G. Holmes – Physical Review Physics Education Research, 2024
Physics education researchers are interested in using the tools of machine learning and natural language processing to make quantitative claims from natural language and text data, such as open-ended responses to survey questions. The aspiration is that this form of machine coding may be more efficient and consistent than human coding, allowing…
Descriptors: Physics, Educational Researchers, Artificial Intelligence, Natural Language Processing
Weinstein, Theresa J.; Ceh, Simon Majed; Meinel, Christoph; Benedek, Mathias – Creativity Research Journal, 2022
Evaluating creativity of verbal responses or texts is a challenging task due to psychometric issues associated with subjective ratings and the peculiarities of textual data. We explore an approach to objectively assess the creativity of responses in a sentence generation task to (1) better understand what language-related aspects are valued by…
Descriptors: Creativity, Sentences, Natural Language Processing, Computation