In the process of textual information analysis, like in the domain of technological survey through patents analysis, or in the domain of emerging research tracking through research papers analysis, the complexity of the studied concepts and the accuracy of the questions to be answered may often lead the analyst to partition his reasoning into viewpoints. Most of the classical information analysis tools can only manage an analysis of the studied domain in a global way. The information analysis paradigm considered in this paper is an alternative paradigm called multi-view data analysis. This paradigm introduces the dimensions of viewpoints and dynamics into information analysis with its multi-view displays, its online generalization capabilities, and its inter-view communication process. The dynamic information exchange between views can be exploited, either by an analyst or in an unsupervised way, in order to perform cooperative deduction between several different analyzes that have been performed on the same data or on related data. This paper demonstrates the efficiency of a viewpoint-oriented analysis as compared to a global analysis in the domain of technological survey and research evaluation. Both objective and subjective quality criteria are taken into account for quality evaluation.