After having her first paper accepted at the IEEE International Conference on Big Data (IEEE BigData 2020), Vanja Ljevar (2017 cohort) announced that her second paper Perception Detection Using Twitter was accepted as well.
ABSTRACT: Patients’ perceptions about their condition have a strong impact on not only adherence to medication but also on how they view themselves in the light of their condition. Research implies that Twitter is particularly a rich source of perceptions as patients frequently use the internet for information sharing and support. However, Twitter contains a lot of noise in the form of tweets that do not relate to perceptions but are rather generated to advertise research and corporate news and this kind of information could `pollute’ perception analysis. This study examines methods that could be used to extract perception tweets, on the example of tweets related to asthma. We first demonstrate differences between perception and non-perception tweets in terms of their linguistic features and then focus on filtering perceptions using the classification process. Results demonstrate that there is a significant difference between perceptions and non-perceptions: perception tweets are shorter, have less capital letters, less punctuation signs and less hashtags. These features also perform well in detecting perceptions. However, the bag of words approach had better results in distinguishing between perception and non-perception tweets and the best results were obtained using word-based frequency vectorization and by training a neural network-based classifier. Future research could explore the synergy of these approaches.
The 2020 IEEE International Conference on Big Data (IEEE BigData 2020) will be taking place online 10-13 December 2020
Great work, Vanja!
Originally posted at https://cdt.horizon.ac.uk/2020/11/18/second-paper-accepted-at-ieee-bigdata-2020/