Zobrazeno 1 - 10
of 2 187
pro vyhledávání: '"WILLIAMS HYWEL"'
This study explores how different weather conditions influence public sentiment on social media, focusing on Twitter data from the UK. By considering climate and linguistic baselines, we improve the accuracy of weather-related sentiment analysis. Our
Externí odkaz:
http://arxiv.org/abs/2407.07683
Researchers commonly perform sentiment analysis on large collections of short texts like tweets, Reddit posts or newspaper headlines that are all focused on a specific topic, theme or event. Usually, general-purpose sentiment analysis methods are use
Externí odkaz:
http://arxiv.org/abs/2307.07864
Online discourse covers a wide range of topics and many actors tailor their content to impact online discussions through carefully crafted messages and targeted campaigns. Yet the scale and diversity of online media content make it difficult to evalu
Externí odkaz:
http://arxiv.org/abs/2303.16694
Online communication about climate change is central to public discourse around this contested issue. Facebook is a dominant social media platform known to be a major source of information and online influence, yet discussion of climate change on the
Externí odkaz:
http://arxiv.org/abs/2211.13965
Autor:
Williams Hywel
Publikováno v:
Indian Journal of Dermatology, Vol 54, Iss 2, Pp 118-123 (2009)
Evidence-based dermatology is the application of high-quality evidence to the care of individual patients with skin diseases. The Centre of Evidence-Based Dermatology in the UK promotes activities in this field through its three interlinking cogs, co
Externí odkaz:
https://doaj.org/article/78248934037942caa0dd52ccd5b86c64
Co-authorship networks, where nodes represent authors and edges represent co-authorship relations, are key to understanding the production and diffusion of knowledge in academia. Social constructs, biases (implicit and explicit), and constraints (e.g
Externí odkaz:
http://arxiv.org/abs/2207.09800
Autor:
Huang, Leo, Tang, Wai Hoh, Attar, Rahman, Gore, Claudia, Williams, Hywel C., Custovic, Adnan, Tanaka, Reiko J.
Publikováno v:
In Artificial Intelligence In Medicine October 2024 156
Autor:
Pande, Ira, Tang, Ting Seng, Tran, Gui, Layton, Alison, Price, Elizabeth, Whittam, Lindsay, Venkatachalam, Srinivasan, Huws, Gwenan, Pratt, Arthur, Reynolds, Nick J, Youngstein, Taryn, Walsh, David A, Joseph, Theresa, Mathew, Rengi, Oikonomou, Stamatios, Gwynne, Catherine, Crowder, Rory, Saravanan, Vadivelu, Mustafa, Alaa, Tacu, Cristina, George, Emmanuel, Batty, Thomas, Soni, Anushka, Horton, Sarah, Gaffney, Karl, Gullick, Nicola, Lapin, Agnieszka, Bingham, Sarah, Madan, Ayesha, Holroyd, Chris, Lwin, May, Khalid, Salema, Green, Mike, Hunt, Laura, Alcorn, Nicola, Ellis, Rob, Hider, Samantha, Hassan, Ala, Douglas, Karen, Ho, Gen Nen, Levasseur, Kirsty, Pradeep, John, Rhys-Dillon, Ceril, Jones, Catrin, Abhishek, Abhishek *, Peckham, Nicholas, Pade, Corinna *, Gibbons, Joseph M *, Cureton, Lucy, Francis, Anne, Barber, Vicki, Williams, Jennifer A E, Appelbe, Duncan, Eldridge, Lucy, Julier, Patrick, Altmann, Daniel M, Bluett, James, Brooks, Tim, Coates, Laura C, Rombach, Ines, Semper, Amanda, Otter, Ashley, Valdes, Ana M, Nguyen-Van-Tam, Jonathan S, Williams, Hywel C, Boyton, Rosemary J †, McKnight, Áine †, Cook, Jonathan A †
Publikováno v:
In The Lancet Rheumatology February 2024 6(2):e92-e104
Detecting important events in high volume news streams is an important task for a variety of purposes.The volume and rate of online news increases the need for automated event detection methods thatcan operate in real time. In this paper we develop a
Externí odkaz:
http://arxiv.org/abs/2005.13751
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