Presentation done at the 3rd International Conference on Artificial Intelligence in Electronics Engineering (AIEE 2022)
The presentation occurred at the 3rd International Conference on Artificial Intelligence in Electronics Engineering (AIEE 2022) on January 11, 2022, in Bangkok, Thailand. The core of the research revolved around training a variety of deep learning models using two separate datasets: one focused on news reactions and another dedicated to Facebook reactions.
The ultimate findings highlighted that incorporating the Facebook dataset notably enhanced the models’ performance. Based on the outcomes, the most effective model identified was a 3-layer stacked BiLSTM model, marking a significant advancement in the state-of-the-art models used for this purpose.
References
2022
Sentiment analysis with deep learning models: a comparative study on a decade of Sinhala language Facebook data
Gihan Weeraprameshwara, Vihanga Jayawickrama, Nisansa Silva, and Yudhanjaya Wijeratne
In 2022 The 3rd International Conference on Artificial Intelligence in Electronics Engineering, 2022
The relationship between Facebook posts and the corresponding reaction feature is an interesting subject to explore and understand. To achieve this end, we test state-of-the-art Sinhala sentiment analysis models against a data set containing a decade worth of Sinhala posts with millions of reactions. For the purpose of establishing benchmarks and with the goal of identifying the best model for Sinhala sentiment analysis, we also test, on the same data set configuration, other deep learning models catered for sentiment analysis. In this study we report that the 3 layer Bidirectional LSTM model achieves an F1 score of 84.58% for Sinhala sentiment analysis, surpassing the current state-of-the-art model; Capsule B, which only manages to get an F1 score of 82.04%. Further, since all the deep learning models show F1 scores above 75% we conclude that it is safe to claim that Facebook reactions are suitable to predict the sentiment of a text.
@inproceedings{weeraprameshwara2022sentiment,title={Sentiment analysis with deep learning models: a comparative study on a decade of Sinhala language Facebook data},author={Weeraprameshwara, Gihan and Jayawickrama, Vihanga and de Silva, Nisansa and Wijeratne, Yudhanjaya},booktitle={2022 The 3rd International Conference on Artificial Intelligence in Electronics Engineering},pages={16--22},year={2022},isbn={9781450395489},publisher={Association for Computing Machinery},address={New York, NY, USA},doi={10.1145/3512826.3512829},numpages={7},keywords={NLP, Sinhala, Sentiment Analysis, Deep Learning},location={Bangkok, Thailand},series={AIEE 2022},}
