In this paper we illustrate the use of Data Science techniques to analyse complex human communication. In particular, we consider tweets from leaders of political parties as a dynamical proxy to political programmes and ideas. We also study the temporal evolution of their contents as a reaction to specific events. We analyse levels of positive and negative sentiment in the tweets using new tools adapted to social media. We also train an Artificial Intelligence to recognise the political affiliation of a tweet. The AI is able to predict the origin of the tweet with a precision in the range of 71-75\%, and the political leaning (left or right) with a precision of around 90\%. This study is meant to be viewed as a proof-of-concept of interdisciplinary nature, at the interface between Data Science and political analysis.

中文翻译：

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使用数据科学工具探索一个国家的政治脉动

在本文中，我们说明了使用数据科学技术来分析复杂的人类交流。特别是，我们将政党领导人的推文视为政治计划和思想的动态替代。我们还研究了其内容的时间演变，作为对特定事件的反应。我们使用适用于社交媒体的新工具来分析推文中正面和负面情绪的水平。我们还会训练人工智能以识别推文的政治归属。AI能够以71-75％的精度预测推文的来源，并以90％的精度预测政治倾向（左或右）。在数据科学和政治分析之间的接口上，本研究应被视为跨学科性质的概念证明。