Analysis of human-wildlife interactions from social media and news sources: A hybrid neural network approach

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This project aims to create a hybrid neural network model consisting of Convolution Neural Network (CNN) to extract character level features with Bisectional Long-Short Term Memory (BiLSTM) to analyse and extract rescue and response information from real time Twitter data and news sources.The project will answer the following questions:1. How can the semantics of Tweets and News sources be analysed for sentiment without loss of context?2. How can features such as location be extracted from raw data? How would sequence modelling connect and preserve context of the extracted feature of interest?3. How could the proposed model "remember" past knowledge and connect it with the post-fire response stage of physical wildfire models? 4. How can the insights help build wildfire response and mitigation policies in the UK and India?