Social networking sites are a new ecosystem of social relations in which adolescents follow public figures or influencers: instagrammers, tweeters and youtubers. Their behaviour in the posts they publish become a trend and a model for the new generations. In order to explore these behaviours and their consequences, it is useful to study the behaviour of the 10 instagramers, 10 tweeters and 10 youtubers with the largest number of followers in the world. A mixed method was employed, combining: social media analysis (SNA) methodology executed by monitoring Twitter, Instagram and YouTube accounts and their publications (300 posts with the highest number of likes). The FanapageKarma tool was used to capture data by applying data mining techniques. Subsequently, sentiment analysis was performed using Meaning Cloud software, determining sentiment polarity analysis quantitatively. Finally, a semantic analysis of the content was performed using Nvivo. The results of multi-regression and sentiment’s analysis show clear differences between social networking sites. Twitter is a space for critical analysis of information and social movements, especially climate change. In this space adolescents defend their values and ideology. Instagram is a showcase for fashion and beauty, where brands support an idealised and desirable lifestyle. YouTube is a space for entertainment and comedy. It concludes that despite their differences there is one univocal feature, the effort of influencers to capture audiences and establish parasocial relationships. Las redes sociales son un nuevo ecosistema de relaciones sociales en el que los adolescentes siguen a personajes públicos o «influencers»: «instagramers», «twitteros» y «youtubers». Su comportamiento en los posts que publican se convierte en una tendencia y un modelo para las nuevas generaciones. Para profundizar en estos comportamientos y sus consecuencias, resulta de utilidad estudiar el comportamiento de los 10 «instagramers», 10 «twitteros» y 10 «youtubers» con mayor número de seguidores en el mundo mediante sus publicaciones (300 post con mayor cantidad de likes). Se empleó un método mixto, combinando: la metodología de análisis de medios sociales (SNA) ejecutada mediante la monitorización de cuentas de Twitter, Instagram y YouTube. Se empleó el instrumento de FanapageKarma para captar los datos aplicando técnicas de minería de datos. Posteriormente, se realizó un análisis de sentimiento mediante el software «Meaning Cloud», este determinó el análisis de la polaridad de los sentimientos de forma cuantitativa. Finalmente, se realizó un análisis semántico de los contenidos mediante Nvivo. Los resultados de la multirregresión y el análisis de sentimientos muestran claras diferencias entre las redes sociales. Twitter es un espacio de análisis crítico de la información y de los movimientos sociales, especialmente del cambio climático. En este espacio los adolescentes defienden sus valores e ideología. Instagram es un escaparate de moda y belleza, donde las marcas apoyan un estilo de vida idealizado y deseable. YouTube es un espacio para el entretenimiento y la comedia. Se concluye que a pesar de sus diferencias hay una característica unívoca, el esfuerzo de los «influencers» por captar audiencias y establecer relaciones parasociales.

The concept of intelligence has been extensively studied, undergoing an evolution from a unitary concept to a more elaborate and complex multidimensional one. In addition, several research studies have focused their efforts for decades on the study of intelligence as a predictor of academic performance of students at different educational stages, being a stable and highly relevant predictor along with other variables such as executive functions, social context, culture or parental guardianship. Thus, the present study, based on a systematic review and meta-analysis, includes 27 studies with a total sample of 42,061 individuals. The main objective was to analyse the relationship between intelligence and academic performance using different predictive models that include moderating variables such as country of origin, type of intelligence, gender and age. The findings of this research highlight the significant, positive and moderate relationship between intelligence and academic performance (r = 0.367; p < 0.001), highlighting the predictive capacity on school performance when the type of intelligence (general and implicit; 35%) or the country of origin (45%) is taken as a moderating variable, with the explanatory models on age or sex not being significant. Therefore, it can be concluded that intelligence, in addition to being a good predictor of academic performance, is influenced depending on the type of intelligence or theoretical model taken as a reference, and also depending on the country or culture of origin.

Despite the obvious favorable effects of social networking sites, there is a risk of developing behavioral addictions. This study aims to analyze addiction to social networks and its relationship with anxiety. A sample (n = 361) of university students (undergraduate, master’s and doctoral) comprising 87.5% women and 12.5% men with a mean age of 32.58 (SD = 12.03) and 32.36 (SD = 10.21), respectively, was included. Addiction to social networks was measured using the Social Network Addiction (SNA) questionnaire and anxiety was measured using Spanish adaptation of the Beck Anxiety Inventory (BAI Test). The regression results show how concurrent moderating variables such as age (adulthood) predispose individuals to addiction in some way (Model 5, explained 13.5%, R²= 0.135, p = 0.040). Similarly, we found that the aspect of addiction that generates anxiety is an obsession with social networks. Anxiety arises as excessive use decreases, similar to abstinence syndrome. It is concluded that the harmlessness of social networks and their inappropriate use can lead to behavioral addiction.