social networks

5 June 2023

Social network addiction in young people has been extensively studied and associated with multiple factors. Among the scales de­signed to measure this, the 24-item version of the Social Network Addiction Questionnaire (SNAQ) is one of the most widely used. This study analyses the psychometric properties of the Spanish version adapted to undergradu­ates. The content and construct validity of the scale was explored using the Rasch model and a confirmatory factor analysis. The data cate­gorisation structure, construct dimensionality, model fit, subject and item reliability, Wright Map structure, and differential item function­ing (DIF) were specifically analysed. 1,809 students from 24 Spanish universities partic­ipated. The results indicate that the SNAQ presents good reliability and dimensionality, and a good model fit; however, elements in need of improvement are appreciated mainly in the proposed Likert scale, in the develop­ment of new items that measure the extremes of addiction to social network sites and in the wording of one item. With respect to fac­tor analysis, three factors were obtained thatcoincide with the original construct. With the improvements that have been observed through validation, the questionnaire could confidently be used to measure the construct in the university population. The instrument fills an important gap in the identification of addictive behaviours in the use of social net­works, which could lead to a subsequent inter­vention involving undergraduates.

Please, cite this article as follows: Suárez-Perdomo, A., Garcés-Delgado, Y., García-Álvarez, E. y Ruiz-Alfonso, Z. (2023). Propiedades psicométricas del cuestionario de adicción a las redes sociales (ARS) a población universitaria | Psychometric properties of the Social Network Addiction Questionnaire (SNAQ) for undergraduates. Revista Española de Pedagogía, 81 (285), 361-379.

21 December 2016

This article analyses the impact of the MOOC movement on the Twitter social network. To do so the lexical-semantic impact of 55,511 tweets by ten of the world’s leading platforms offering MOOC courses was analysed using a tf-idf calculation to represent documents in natural language processing.

The Twitter profiles, patterns of use, and geolocation of tweets by continent were also analysed using computational and statistical techniques. The results show that there is no correlation between use of Twitter accounts by MOOC platforms and their number of followers.

The tweets by participants are mainly grouped into two semantic blocks: alert/ excited and calm/relaxed and tweet traffic is often concentrated in the United States and Europe; South America’s percentage is moderate while Africa, Asia and Oceania have little impact. The most frequently occurring words in the tweets are: «learning», «skills», «course», «free» and «online».



Cite this article as: Vázquez-Cano, E., López Meneses, E., & Sevillano García, M. L. (2017).  La repercusión del movimiento MOOC en las redes sociales. Un estudio computacional y estadístico en Twitter | The impact of the MOOC movement on social networks. A computational and statistical study on Twitter. Revista Española de Pedagogía, 75 (266), 47-64. doi: