Automatic Opinion Extraction from Football-Related Social Media: a Gazetteer and Rule-Based Approach

EasyChair Preprint no. 11571

Abstract

Sentiment analysis on social networks has become a highly active area of research in recent years. With the explosion of social media and the massive amount of user-generated data, it has become crucial to understand the opinions and sentiments expressed online. Sentiment analysis is used to categorize expressed feelings in various ways, such as negative, positive, or neutral. The aim of this work is to enhance techniques for researching and extracting opinions. The main idea is to identify opinions within a set of documents or texts available online for exploitation by other systems. In this study, we present an approach based on an opinion detection system on social networks (Facebook) regarding the UEFA Champions League. The implementation of this solution was carried out using the GATE platform (General Architecture for Text Engineering). This work thus contributes to the field of sentiment and opinion analysis in social networks by employing Gazetteers and leveraging the JAPE rules (Java Annotation Patterns Engine).

Keyphrases: Gazetteer, Rules JAPE, Sentiment Analysis, social networks

@Booklet{EasyChair:11571,
  author = {Atmane Hadji and Mohmed-Khireddine Kholladi},
  title = {Automatic Opinion Extraction from Football-Related Social Media: a Gazetteer and Rule-Based Approach},
  howpublished = {EasyChair Preprint no. 11571},

  year = {EasyChair, 2023}}