As the usage of social media has increased, the size of shared data has instantly surged and this has been an important source of research for environmental issues as it has been with popular topics. Sentiment analysis has been used to determine people's sensitivity and behavior in environmental issues. However, the analysis of Turkish texts has not been investigated much in literature. In this article, sentiment analysis of Turkish tweets about global warming and climate change is determined by machine learning methods. In this regard, by using algorithms that are determined by supervised methods (linear classifiers and probabilistic classifiers) with trained thirty thousand randomly selected Turkish tweets, sentiment intensity (positive, negative, and neutral) has been detected and algorithm performance ratios have been compared. This study also provides benchmarking results for future sentiment analysis studies on Turkish texts.

中文翻译：

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数据挖掘方法对Twitter全球变暖共享推文的情感分析：以土耳其语为例。

随着社交媒体使用量的增加，共享数据的大小迅速激增，这已经成为研究环境问题的重要来源，因为它已经成为热门话题。情感分析已被用来确定人们在环境问题上的敏感性和行为。但是，土耳其文本的分析在文学中并未得到太多研究。在本文中，通过机器学习方法确定了有关全球变暖和气候变化的土耳其推文的情绪分析。在这方面，通过使用由受监督的方法（线性分类器和概率分类器）确定的算法，以及经过训练的三万条随机选择的土耳其推文，已检测到情绪强度（正，负和中性），并对算法性能比进行了比较。