Abstract Advertising researchers and practitioners are increasingly using social media analytics (SMA), but focused overviews that explain how to use various SMA techniques are scarce. We focus on how researchers and practitioners can computationally analyze topics of conversation in social media posts, compare each to a human-coded topic analysis of a brand’s Twitter feed, and provide recommendations on how to assess and choose which computational methods to use. The computational methodologies that we survey in this article are text preprocessed summarization, phrase mining, topic modeling, supervised machine learning for text classification, and semantic topic tagging.

中文翻译：

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计算分析社交媒体文本的主题：广告研究人员入门

摘要广告研究人员和从业人员越来越多地使用社交媒体分析（SMA），但缺乏解释如何使用各种SMA技术的集中概述。我们专注于研究人员和从业人员如何计算分析社交媒体帖子中的会话主题，将每个主题与品牌的Twitter提要的人工编码主题分析进行比较，并提供有关如何评估和选择使用哪种计算方法的建议。我们在本文中调查的计算方法是文本预处理摘要，短语挖掘，主题建模，用于文本分类的监督机器学习和语义主题标记。