Modelling and Sentiment Analysis of Game Reviews

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Nowadays, companies have access to an unprecedented amount of data from their users. However, extracting the knowledge that these companies need has proven to be a challenging task, and the gaming industry is not an exception. Traditional classification algorithms, such as Logistic regression and Naïve Bayes, as well as more recent ones that use (Deep) Neural Networks, such as Recurrent Neural Networks (RNNs) based algorithms, and the SotA algorithms, such as attention models, are three classes of algorithms that are frequently used for such applications. While the traditional algorithms are the most interpretable, the latter two have superior performance. During my PhD, I aim to investigate each of these algorithms for modelling and sentiment analysis of game reviews on social media. These results are aimed to be used by the game industry to better analyse their users' feedback and utilise various NLP tools to enhance their user experience.