Listen to the Noise: Demonstrating an End to End Multi-platform and Multilingual Sentiment Analysis Approach

Daniel Anusic, Abid Hussain*

*Corresponding author for this work

Research output: Contribution to journalConference article in journalResearchpeer-review

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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.
Original languageEnglish
JournalProcedia Computer Science
Volume219
Pages (from-to)546-553
Number of pages8
ISSN1877-0509
DOIs
Publication statusPublished - 2023
EventCENTERIS 2022: International Conference on ENTERprise Information Systems - Lisbon, Portugal
Duration: 9 Nov 202211 Nov 2022
Conference number: 14
http://centeris.scika.org/#

Conference

ConferenceCENTERIS 2022
Number14
Country/TerritoryPortugal
CityLisbon
Period09/11/202211/11/2022
Internet address

Keywords

  • Sports industry
  • Multilingual sentiment analysis
  • Social media analysis
  • Natural language processing
  • Machine learning

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