Presentation done at the 2021 International Conference on Advances in ICT for Emerging Regions (ICTer 2021).
The presentation took place at the 21st International Conference on Advances in ICT for Emerging Regions (ICTer 2021) on December 2nd, 2021, held virtually amid the COVID-19 pandemic. During this session, introduction of two innovative models: the Core Reaction Set model and the All Reaction Set model was happened. These models were designed to enhance reaction prediction for Facebook posts.
The focus of the presentation was to demonstrate the efficacy of these models, individually and in combination with the Star Rating model. By comparing the outcomes, we aimed to analyze their impact on predicting user reactions to Facebook posts.
References
2021
Seeking Sinhala Sentiment: Predicting Facebook Reactions of Sinhala Posts
Vihanga Jayawickrama, Gihan Weeraprameshwara, Nisansa Silva, and Yudhanjaya Wijeratne
In 2021 21st International Conference on Advances in ICT for Emerging Regions (ICter), 2021
The Facebook network allows its users to record their reactions to text via a typology of emotions. This network, taken at scale, is therefore a prime data set of annotated sentiment data. This paper uses millions of such reactions, derived from a decade worth of Facebook post data centred around a Sri Lankan context, to model an eye of the beholder approach to sentiment detection for online Sinhala textual content. Three different sentiment analysis models are built, taking into account a limited subset of reactions, all reactions, and another that derives a positive/negative star rating value. The efficacy of these models in capturing the reactions of the observers are then computed and discussed. The analysis reveals that binary classification of reactions, for Sinhala content, is significantly more accurate than the other approaches. Furthermore, the inclusion of the like reaction hinders the capability of accurately predicting other reactions.
@inproceedings{jayawickrama2021seeking,title={Seeking Sinhala Sentiment: Predicting Facebook Reactions of Sinhala Posts},author={Jayawickrama, Vihanga and Weeraprameshwara, Gihan and de Silva, Nisansa and Wijeratne, Yudhanjaya},booktitle={2021 21st International Conference on Advances in ICT for Emerging Regions (ICter)},pages={177--182},year={2021},organization={IEEE},doi={10.1109/ICter53630.2021.9774796},}
