نبذة مختصرة : Label what is and what is not news is part of the basic tasks of any journalist. As much as these assessments are commonplace and able to cope with the pressures of time and resources, they fail to take advantage of the knowledge processed to reflect on their own effectiveness, as well as to generate organizational advantages and accountability tools. Interested in the quality of journalistic production, this work aims to contribute to the experimental development of a methodology for evaluating the journalistic relevance which, in the opposite way, to be able to generate data about themselves and to instrumentalize other advances. Such methodology is embedded in a newspaper production management software called Qualijor, which has, among other structures, a specific matrix for assessing relevance. Due to the period of software experimental development, which is already a prototype, the contribution in question relates to a trial of its structure and adds some useful conceptual basis for the interpretation of evaluative data and possible future enhancements. Before performing the experimental evaluation that the work is proposed, however, it is necessary to deepen the treatment of term relevance, reflecting not only on its definition, but also on the knowledge that the tangent, notably the news values, which are presented as indicators relevance. It is still necessary to place the relevance, as defined, in a proposal for evaluation of editorial quality that reflects commitments to media accountability and bring the requirement and the software of an organizational knowledge management proposal. As the methodological procedures, the work can be described as an experimental research development, testing the effectiveness of a prototype by conducting an experiment. During the experimental evaluation were analyzed 180 newspaper articles that occupied several prominent position in three important communication vehicle of online, print and television media. Seeking to realize an increase in data generation and ...
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