In this paper we propose a decision-making procedure where the agents judge the alternatives through linguistic terms such as 'very good', 'good', 'acceptable', etc. If the agents are not confident about their opinions, they can use a linguistic expression formed by several consecutive linguistic terms. To obtain a ranking on the set of alternatives, the method consists of three different stages. The first stage looks for the alternatives in which the overall opinion is closer to the ideal assessment. The overall opinion is developed by a distance-based process among the individual assessments. The next two stages form a tie-breaking process. Firstly by using a dispersion index based on the Gini coefficient, and secondly by taking into account the number of best-assessments. The main characteristics of the proposed decision-making procedure are analyzed.

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In this chapter, we propose a multi-person decision making procedure where agents judge the alternatives through linguistic expressions generated by an ordered finite scale of linguistic terms (for instance, 'very good', 'good', 'acceptable', 'bad', 'very bad'). If the agents are not confident about their opinions, they might use linguistic expressions composed by several consecutive linguistic terms (for instance, 'between acceptable and good'). The procedure we propose is based on distances and it ranks order the alternatives taking into account the linguistic information provided by the agents. The main features and properties of the proposal are analyzed.

In this paper, we study different methods of scoring linguistic expressions defined on a finite set, in the search for a linear order that ranks all those possible expressions. Among them, particular attention is paid to the canonical extension, and its representability through distances in a graph plus some suitable penalization of imprecision. The relationship between this setting and the classical problems of numerical representability of orderings, as well as extension of orderings from a set to a superset is also explored. Finally, aggregation procedures of qualitative rankings and scorings are also analyzed.

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