A decision making model to evaluate the reputation in social networks using HFLTS

We present Teranga Go!, a social network with a linguistic fuzzy model which deals with HFLTS information as a practical application of decision making problems. It is defined to help members to select to whom interact based on collective information regarding real interactions with any user. In this way, we provide a tool intended to build trust among members of a sharing economy community given that is a major drawback from online transactions. As a workbench to run the linguistic decision making model, a web site and a mobile application for iOS and Android offer access to a carpooling service named Teranga Go! that seek to foster the mobility of international migration flows from Europe to Africa, based on concepts of collaborative economy and participatory consumption. The novelty of the site is the possibility of using hesitant linguistic expressions to assess a set of qualitative criteria and the use of the community members as the pool of experts. Unlike many multi criteria decision making problems we do not rank alternatives, we just qualify them using the retrieved opinions, which target a given user, and are collected over any interaction with this person along the time. Based on Computing with Words methodology where inputs are words and output are also words, we obtain from the model a linguistic value that is used to represent a karma property present in the user profile.