Twitter is a social media platform bridging most countries and allows real-time news discovery. Since the tweets on Twitter are usually short and express public feelings, thus provide a source for opinion mining and sentiment analysis for global events. This paper proposed an effective solution, in providing a sentiment on tweets related to the FIFA World Cup. At least 130k tweets, as the first in the community, are collected and implemented as a dataset to evaluate the performance of the proposed machine learning solution. These tweets are collected with the related hashtags and keywords of the Qatar World Cup 2022. The Vader algorithm is used in this paper for sentiment analysis. Through the machine learning method and collected Twitter tweets, we discovered the sentiments and fun facts of several aspects important to the period before the World Cup. The result shows people are positive to the opening of the World Cup.

翻译：推特作为连接多数国家的社交媒体平台，能够实现实时新闻发现。由于推文通常简短且反映公众情感，因此为全球性事件的舆论挖掘和情感分析提供了数据源。本文提出了一种有效解决方案，用于分析世界杯相关推文的情感倾向。作为社区内首次尝试，我们收集了至少13万条推文作为数据集，以评估所提出的机器学习解决方案的性能。这些推文通过2022年卡塔尔世界杯的相关话题标签和关键词进行采集。本文采用Vader算法进行情感分析。通过机器学习方法及所采集的推文数据，我们发现了世界杯开幕前若干重要方面的情感倾向与趣味事实。结果表明，人们对世界杯开幕持积极态度。