From motivation and self-structure to a decision support framework for online social networks

• Autor(a) principal: Antunes, Francisco
• Data de Publicação: 2018
• Outros Autores: Freire, Manuela, Costa, João Paulo
• Tipo de documento: Artigo
• Idioma: eng
• Título da fonte: Repositórios Científicos de Acesso Aberto de Portugal (RCAAP)
• Texto Completo: http://hdl.handle.net/10400.6/4596
• topic: Case Study; Data Extraction; Decision-Making; Group; Online Social Network; Semantics; Social Network Analysis

Data collected from online social networks offers new possibilities for supporting organizations’ daily activities. It is also common knowledge that the opinion exchange in online social networks provides a decisive contribution in decision making. It is, thus, necessary to review and bare present the motivations by which people engage in online social network and the ways in which firms can make use of such motivations in order to take advantage of online social networks as information sources for decisionmaking support. To do so, the authors of this chapter developed the decision-support social networks to extract such information, which encompasses the intertwined use of human interaction and network structure by combining human capabilities, social network analysis (SNA), and automatic data mining. In this chapter, a brief summary of the performed case studies over the proposed information model is also presented.