The object of this research is to exploit the algorithm of Twitter’s trending topic (TT) and identify the elements capable of guiding public opinion in the Italian panorama. The underlying hypotheses that guide the whole article, confirmed by the research results, concern the existence of (a) a limited number of elements at the base of each popular hashtag with very high viral power and (b) hashtags transversal to the themes detected by the Twitter algorithm that define specific opinion polls. Through computational techniques, it was possible to extract and process data sets from six specific hashtags highlighted by TT. In a first step through social network analysis, we analyzed the hashtag semantic network to identify the hashtags transversal to the six TTs. Subsequently, we selected for each data set the contents with high sharing power and created a “potential opinion leader” index to identify users with influencer characteristics. Finally, a cross section of social actors able to guide public opinion in the Twittersphere emerged from the intersection between potentially influential users and the viral contents.

本研究的目的是利用 Twitter 的热门话题 (TT) 算法，确定能够在意大利全景中引导舆论的元素。研究结果证实了指导整篇文章的基本假设，涉及 (a) 每个流行标签底部的元素数量有限，具有非常高的病毒传播力，以及 (b) 与检测到的主题横向的标签定义特定民意调查的 Twitter 算法。通过计算技术，可以从 TT 突出显示的六个特定主题标签中提取和处理数据集。在社交网络分析的第一步中，我们分析了话题标签语义网络，以识别横向于六个 TT 的话题标签。随后，我们为每个数据集选择了具有高分享力的内容，并创建了“潜在意见领袖”指数，以识别具有影响者特征的用户。最后，在具有潜在影响力的用户和病毒式内容之间的交叉点中出现了能够在 Twitter 领域引导公众舆论的跨部门社会参与者。