Popularity in social media is mostly interpreted by drawing a relationship between a social media account and its followers. Although understanding popularity from social media has been explored for about a decade, to our knowledge, the extent to which the account owners put efforts to enhance their popularity has not been evaluated in detail. In this paper, we focus on Twitter, a popular social media, and consider the case study of the 2016 US elections. More specifically, we aim to assess whether candidates endeavor to improve their style of tweeting over time to be more attractive to their followers. An ad hoc-defined predictive model based on a recurrent random forest is used for this purpose. To this end, we build a classification model whose features are obtained from the characteristics of a set of content/sentiment information extracted from the tweets. Next, we derive an index of social media popularity for both candidates. Results show that Trump wisely exploited Twitter to attract more people by tweeting in a well-organized and desirable manner and that his tweeting style has increased his popularity in social media. The differences in the tweeting styles of the two presidential candidates and the links between the sentiments arising from candidates’ tweets and their popularity index are also investigated.

中文翻译：

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循环随机森林用于评估社交媒体的受欢迎程度

社交媒体中的流行度通常是通过在社交媒体帐户及其追随者之间建立关系来解释的。尽管已经探索了从社交媒体了解受欢迎程度的方法，但是据我们所知，尚未详细评估帐户所有者为提高其受欢迎程度所做的努力。在本文中，我们重点关注流行的社交媒体Twitter，并考虑2016年美国大选的案例研究。更具体地说，我们旨在评估求职者是否努力改善其推文风格，以使其对追随者更具吸引力。为此，使用了基于递归随机森林的临时定义的预测模型。为此，我们建立了一个分类模型，该模型的特征是从推文中提取的一组内容/情感信息的特征中获得的。接下来，我们得出两个候选人的社交媒体受欢迎程度指数。结果表明，特朗普通过有条理和可取的方式在推特上明智地利用Twitter吸引了更多人，他的推特风格增加了他在社交媒体中的知名度。还研究了两位总统候选人的推文风格的差异以及候选人的推文与其人气指数之间的联系。结果表明，特朗普通过有条理和可取的方式在推特上明智地利用Twitter吸引了更多人，他的推特风格增加了他在社交媒体中的知名度。还研究了两位总统候选人的推文风格的差异以及候选人的推文与其人气指数之间的联系。结果表明，特朗普明智地利用Twitter以一种井井有条，令人向往的方式发推特，从而吸引了更多人，他的推特风格增加了他在社交媒体中的知名度。还研究了两位总统候选人的推文风格的差异以及候选人的推文与其人气指数之间的联系。