This dataset includes the evaluation of The New York Times newsletters conducted in March 2023. The analysis applies the Curation Analysis System (CAS) methodology, developed by Guallar et al. (2021b), which provides a structured framework for assessing curated journalistic content. The dataset is part of the project "Parameters and Strategies to Increase the Relevance of Media and Digital Communication in Society: Curation, Visualisation, and Visibility (CUVICOM)" (PID2021-123579OB-I00), funded by the Ministry of Science and Innovation.

Files Included: FinalScores.xlsx Description: This file contains the scoring results for The New York Times newsletters. The file includes multiple tabs that organise the data into: Overall Scores: Aggregated scores assigned to each newsletter based on the evaluation criteria. Scores by Section: Breakdown of scores by specific sections or categories of newsletters. Rankings by Item: Rankings derived from individual parameters in the scoring rubric. Purpose: To provide a quantitative assessment of newsletter performance using the CAS methodology. CodingSheet_CAS_Methodology.pdf

Description: This document details the Curation Analysis System (CAS) method. It outlines the two primary dimensions of analysis: Content Dimension: Evaluates aspects such as the quantity of curated content, its time range (e.g., retrospective or real-time), origin (internal or external), and source characteristics (type and format). Curation Dimension: Focuses on curatorial processes, including authorship visibility, techniques like summarising or quoting, and the journalistic purpose of links (e.g., informing or contextualising). Purpose: To guide the evaluation process by defining the parameters and procedures used in scoring and analysis.