Differently from traditional transaction data, social media data are difficult to investigate due to their volume, variety and velocity. Indeed, the knowledge extraction from social media data raises several issues especially for what concerns statistical exploration and synthesis of complex information. Our work aims to study users' preferences, stated on a social media platform, in order to aid businesses to make their marketing communication decisions. We rely our analysis upon 5685 Italian Facebook users interested in pharmaceutical products and health. The data have been collected at the end of 2014 and are focused on Likes actively expressed by the subjects on specific categories of interests (TV Channels and Magazines). Through a factorial analysis we uncovered significant associations between marketing communication Media and users' profiles. This allows sketching out a marketing strategy in twofold actions: first, identifying the target group to reach and, then, the nearest suitable channel where to develop the marketing communication.

与传统交易数据不同，社交媒体数据由于其数量，种类和速度而难以调查。确实，从社交媒体数据中提取知识提出了几个问题，特别是涉及统计探索和复杂信息综合的问题。我们的工作旨在研究在社交媒体平台上陈述的用户偏好，以帮助企业做出营销传播决策。我们的分析基于对药品和健康感兴趣的5685名意大利Facebook用户。数据已于2014年底收集，重点关注主题在特定兴趣类别（电视频道和杂志）上积极表达的喜欢。通过析因分析，我们发现了营销传播媒体与用户之间的重要联系。个人资料。这样就可以从两个方面勾勒出一种营销策略：首先，确定要到达的目标人群，然后，确定用于进行营销传播的最近的合适渠道。