We propose a text classification tool based on support vector machines for the assessment of organizational leadership styles, as appearing to Twitter users. We collected Twitter data over 51 days, related to the first 30 Italian organizations in the 2015 ranking of Forbes Global 2000-out of which we selected the five with the most relevant volumes of tweets. We analyzed the communication of the company leaders, together with the dialogue among the stakeholders of each company, to understand the association with perceived leadership styles and dimensions. To assess leadership profiles, we referred to the 10-factor model developed by Barchiesi and La Bella in 2007. We maintain the distinctiveness of the approach we propose, as it allows a rapid assessment of the perceived leadership capabilities of an enterprise, as they emerge from its social media interactions. It can also be used to show how companies respond and manage their communication when specific events take place, and to assess their stakeholder's reactions.

翻译：我们提议了一个基于支持矢量机的文本分类工具,用于评估组织领导风格,如Twitter用户所看到的。我们收集了51天的Twitter数据,涉及2015年Forbes Global 2000排名中的头30个意大利组织,我们从中选择了5个组织及其最相关的推文数量。我们分析了公司领导人的沟通以及每家公司利益攸关方之间的对话,以了解与人们所认为的领导风格和层面的联系。为了评估领导层概况,我们提到了2007年由Barchiesi和La Bella开发的10个因素模型。我们保持了我们建议的方法的独特性,因为它使得能够快速评估一个企业从其社交媒体互动中发现的领导能力。我们还可以用来显示公司在具体事件发生时如何应对和管理其沟通,并评估其利益攸关方的反应。