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.
翻译:在本文中,我们用数据科学技术来分析复杂的人类交流。我们尤其认为政党领导人的推文是政治纲领和思想的动态替代物。我们还研究其内容的时空演变,作为对具体事件的反应。我们利用适应社会媒体的新工具分析推文中的正负情绪水平。我们还培训人工智能,以识别推文的政治属性。大赦国际能够精确地预测推文的来源,范围为71-75 ⁇,政治倾斜(左倾或右倾),精确度约为90 ⁇ 。这项研究旨在被视为数据科学与政治分析界面的跨学科概念的证明。