Results demonstrate that the developed DNN model successfully identified climate change deniers based on tweet contents with an overall accuracy of 88%. There ...
The objectives are: (1) to develop an optimized Deep Neural Network (DNN) classifier to identify users who are climate change deniers based on tweet contents; ( ...
Exploring climate change on Twitter using seven aspects: Stance, sentiment, aggressiveness, temperature, gender, topics, and disasters · Environmental Science.
In this study, we focus on identifying content on Twitter that denies climate change and often leads to a delay in appropriate climate action by performing an ...
Sep 21, 2022 · Detecting climate change deniers on twitter using a deep neural network. In Proceedings of the 2019 11th International Conference on Machine ...
Nov 7, 2022 · DNN (Chen, Zou, and Zhao 2019): Deep Neural Network. (DNN) is used as a classifier to identify users who either be- lieve or deny climate change ...
Aug 16, 2024 · The Augmented Computer Assisted Recognition of Denial and Skepticism (CARDS) model is specifically designed for categorising climate claims on Twitter.
Missing: Neural Network.
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Feb 15, 2024 · The scientists used a Deep Learning text recognition model to classify 7.4 million tweets containing climate change-related keywords, which ...
Missing: Neural | Show results with:Neural
DNN. [Chen et al., 2019]: a neural network that classifies users as climate change deniers/believers on Twitter. 6 Results. We report the results with respect ...
Jul 25, 2024 · The objective of the study was to examine a vast dataset of over 11 million English-language tweets concerning climate change gathered over an eleven-year ...