Abstract
This paper demonstrates a holistic approach for conducting multi-platform and multilingual sentiment analysis of a main stream football club in the United Arab Emirates. The paper reports first iterations of the research project which anticipates to build an automated sentiment analysis system for football clubs to detect and prevent a potential social media crisis at an early stage. The article illustrates a schematic of how state of the art machine learning algorithms, methods and techniques can be put together to provide a basis for automated data collection, classification, sentiment analysis and visual reporting. The article also presents that the time-consuming and costly process of human text labelling can be effectively replaced by lexicon-based sentiment analysis.
This paper reports the complete process from data collection to visual reports to discuss challenges and opportunities associated with design and development of such artefacts.
This paper reports the complete process from data collection to visual reports to discuss challenges and opportunities associated with design and development of such artefacts.
Original language | English |
---|---|
Journal | Procedia Computer Science |
Volume | 219 |
Pages (from-to) | 546-553 |
Number of pages | 8 |
ISSN | 1877-0509 |
DOIs | |
Publication status | Published - 2023 |
Event | CENTERIS 2022: International Conference on ENTERprise Information Systems - Lisbon, Portugal Duration: 9 Nov 2022 → 11 Nov 2022 Conference number: 14 http://centeris.scika.org/# |
Conference
Conference | CENTERIS 2022 |
---|---|
Number | 14 |
Country/Territory | Portugal |
City | Lisbon |
Period | 09/11/2022 → 11/11/2022 |
Internet address |
Keywords
- Sports industry
- Multilingual sentiment analysis
- Social media analysis
- Natural language processing
- Machine learning