We elaborate on the shifting of decision support systems towards social networking, which is based on the concepts of Web 2.0 and Semantic Web technology. As the characteristics of the relevant components are different from traditional decision support systems, we present necessary adaptations when adopting social networks for decision support within an organization. We also present organizational obstacles when adopting/using such systems and clues to overcome them.

The combination between online social networks (OSN) and decision processes provides a favorable social data analysis paradigm for efficient decision support and business-processes integration. This paper presents a framework for handling OSN's contents, providing a simpler and effective approach for information retrieval and processing. The objective is to address a decision-making problem, by using that framework to extract, process, structure and analyze the OSN's data. The decision process is not only guided by OSN data, but also by social network analysis methodology and is entirely based on the communications among social media users. Our framework combines two different, though complementary, perspectives: the analysis of the interactions among users and the semantic analysis of their discourses. In addition, it aims to bridge technology and manual-based approaches, thus enhancing the possibilities for making a better use of an OSN, using free-available software. The case study, herein, aims to estimate customers' requests, solely based on their Facebook posts, showing that the unstructured data of the web's discourse can be used to support this kind of decision processes.