mlsanityData to 14 Oct 2026

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

arXiv 2307.10303 ↗First posted 18 Jul 2023cs.CL cs.LG stat.MLcited by 2

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Abstract (arXiv)

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.

Key facts. Cited by 2 papers in the map (data through 14 Oct 2026). Builds on 3 of its 16 references that are in the map. First posted on arXiv 18 Jul 2023.

Builds on

3 of 16 references.

References · 3

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020TweetEval: Unified Benchmark and Comparative Evaluation for Tweet Classificationcited by 417
  3. 2017State-of-the-art Speech Recognition With Sequence-to-Sequence Modelscited by 196

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2025: 1; 2026: 1.

2 papers.

  1. 2025Posture-Driven Action Intent Inference for Playing style and Fatigue Assessmentcited by 0
  2. 2026SUMMIR: A Hallucination-Aware Framework for Ranking Sports Insights from LLMscited by 0