Alignment of structured and unstructured data for decision support

Since the rising concept of social media, companies try to make use of the information that is provided by these networks. The difficulty of such data lies within their unstructured nature. In order to overcome these boundaries and discover the structure behind such data, managers implement a structuring process that involves other structured data from a company itself, e.g. sales numbers. Managers have bounded rationality, which affects their decision model and ultimately the structuring process. The paper proposes a method that includes an approach to cover the structuring process and enhance the level of relevant structured information. Aside taking into account internal factors and statistical relevance, sentiment analysis plays an important part. The alignment of both data types involves the decrease of redundancies and errors among the process. Additionally, two online tools will in combination with a case prove the feasibility of the method. The case includes information from social media and sentiment estimates on investment moods.