Analyzing sports commentary in order to automatically recognize events and extract insights
Yanis Miraoui

TL;DR
This paper explores the use of various NLP techniques to automatically identify key sports events and extract insights from live commentaries, including the potential role of sentiment analysis.
Contribution
It introduces a comprehensive approach combining multiple NLP methods to classify sports actions and assess sentiment's usefulness in event detection.
Findings
NLP techniques can effectively recognize sports actions from commentaries
Sentiment analysis may enhance event detection accuracy
Different sources provide diverse insights into sports events
Abstract
In this paper, we carefully investigate how we can use multiple different Natural Language Processing techniques and methods in order to automatically recognize the main actions in sports events. We aim to extract insights by analyzing live sport commentaries from different sources and by classifying these major actions into different categories. We also study if sentiment analysis could help detect these main actions.
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Code & Models
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Taxonomy
TopicsSentiment Analysis and Opinion Mining · Advanced Text Analysis Techniques · Topic Modeling
MethodsLinear Layer · Class-MLP · Residual Connection · Weight Decay · Attention Dropout · Linear Warmup With Linear Decay · WordPiece · Adam · Dropout · Softmax
