Search

The aim of this qualitative study was to uncover homogeneity (commonalities between adolescents), heterogeneity (differences between adolescents), and duality (differences within adolescents) in the relationship between adolescents’ social media use and well-being. To do so, 8 focus groups with 55 adolescents aged 14–17 were conducted. Anchored in the differential susceptibility to media effects model, we examined adolescents’ (1) individual motives and (2) moods leading to social media use, (3) the nature of this use, (4) their affective responses, and (5) perceived longer-term effects. Through deductive thematic analysis, we noted large homogeneity in motives for social media use but heterogeneity in moods leading to social media use. In addition, our findings revealed heterogeneity and duality in the affective responses and the perceived long-term effects of social media use. This duality, where the same individual is affected in both positive and negative ways by social media use, appeared in various forms: concurrently , when adolescents experience conflicting feelings simultaneously, such as feeling both envy and inspiration; alternately , when adolescents shift between experiences, such as feelings of connection and isolation; and sequentially , for example, where initial enjoyment gradually turns into boredom. Furthermore, duality appeared across different cognitive and affective aspects of well-being. Directions for future research are provided on how to examine the role and meaning of various forms of homogeneity, heterogeneity, and duality in the relationship between adolescents’ social media use and well-being.

We investigated the expressions of happiness and sadness in adolescents’ direct messages (DMs) on Instagram. Using neural topic modeling ( BERTopic ), we analyzed 211,778 DMs belonging to 96 adolescents, who donated data from 101 Instagram accounts. Results showed that (1) expressions of happiness were more than four times more prevalent than expressions of sadness; (2) the number of DMs containing expressions of happiness and expressions of sadness were highly correlated; (3) there are temporal trends in the expression of happiness and sadness in adolescents’ DMs, and there are individual differences in these trends; and (4) there is no significant between- or within-person relationship between the number of DMs containing expressions of happiness and sadness and adolescents’ well-being.

The formation and maintenance of friendship closeness is an important developmental task in adolescence. To obtain insight in real-time processes that may underlie the development of friendship closeness in middle adolescence, this preregistered experience sampling study [ESM] investigated the effects of social media use on friendship closeness. The study was conducted among 387 adolescents (54% girls; M[subscript age] = 14.11 years; 96% Dutch) from different educational tracks (44% lower prevocational secondary education, 31% intermediate general secondary education, 26% academic preparatory education). Adolescents reported six times per day for 3 weeks on their Instagram, WhatsApp, and Snapchat use in the previous hour and their momentary experiences of friendship closeness (126 assessments; 34,930 observations). Multilevel analyses revealed positive between-person associations of friendship closeness with general WhatsApp use and Instagram use with close friends. In contrast, at the within-person level, we found small negative overall associations of general WhatsApp use and Instagram use (with and without close friends) with friendship closeness. However, there was large heterogeneity in the person-specific effect sizes of the within-person associations of social media use with friendship closeness. For example, person-specific effect sizes of the association of Instagram use with close friends with friendship closeness ranged from [beta] = -0.745 to [beta] = 0.697. These results underline the importance of acknowledging person-specific effects in developmental and media effect theories.

Abstract Research agrees that self-reported measures of time spent with social media (TSM) show poor convergent validity, because they correlate modestly with equivalent objective digital trace measures. This experience sampling study among 159 adolescents (12,617 self-reports) extends this work by examining the comparative predictive validity of self-reported and digital trace measures of TSM, that is, the extent to which self-reported and digital trace measures of TSM correspond in their effects on self-esteem, well-being, and friendship closeness. Using an N = 1 method of analysis, we investigated the correspondence on a between-person, within-person, and person-specific level. Although our results confirmed the poor convergent validity of self-reported TSM reported earlier, we found that self-reports of TSM had comparable predictive validity to digital trace measures on all three levels. Because comparative predictive validity of self-reported TSM is crucial for investigating social media effects, our results have important implications for future research using self-reported TSM.

Abstract Who benefits most from using social media is an important societal question that is centered around two opposing hypotheses: the rich-get-richer versus the poor-get-richer hypothesis. This study investigated the assumption that both hypotheses may be true, but only for some socially rich and some socially poor adolescents and across different time intervals. We employed a state-of-the-art measurement burst design, consisting of a three-week experience sampling study and seven biweekly follow-up surveys. Person-specific analyses of more than 70,000 observations from 383 adolescents revealed that 12% of the socially rich adolescents (high in friendship support or low in loneliness) felt closer to their friends after using social media, as opposed to about 25% of the socially poor adolescents (low in friendship support or high in loneliness). However, only 1 to 6% of all adolescents (socially rich and poor) felt closer both in the short- and longer-term. These results indicate that the rich-get-richer and the poor-get-richer hypotheses can hold both, but for different adolescents.

This study investigated the effects of active private, passive private, and passive public social media use on adolescents' affective well-being. Intensive longitudinal data (34,930 assessments in total) were collected through a preregistered three-week experience sampling method study among 387 adolescents. N = 1 time series were investigated, using Dynamic Structural Equation Modeling. Findings showed that different types of social media use very rarely yielded different effects within one and the same adolescent: 45% of adolescents experienced no changes in well-being due to any of the three types of social media use, 28% only experienced declines in well-being, and 26% only experienced increases in well-being. Only one adolescent experienced the theoretically expected effect pattern of a positive effect of active private and passive private use and negative effect of passive public use. Together, the findings suggest that the active–passive use dichotomy in social media research is less clear-cut than it might seem. [ABSTRACT FROM AUTHOR]

Many post-lingually deafened cochlear implant (CI) users report that they no longer enjoy listening to music, which could possibly contribute to a perceived reduction in quality of life. One aspect of music perception, vocal timbre perception, may be difficult for CI users because they may not be able to use the same timbral cues available to normal hearing listeners. Vocal tract resonance frequencies have been shown to provide perceptual cues to voice categories such as baritone, tenor, mezzo-soprano, and soprano, while changes in glottal source spectral slope are believed to be related to perception of vocal quality dimensions such as fluty vs. brassy. As a first step toward understanding vocal timbre perception in CI users, we employed an 8-channel noise-band vocoder to test how vocoding can alter the timbral perception of female synthetic sung vowels across pitches. Non-vocoded and vocoded stimuli were synthesized with vibrato using 3 excitation source spectral slopes and 3 vocal tract transfer functions (mezzo-soprano, intermediate, soprano) at the pitches C4, B4, and F5. Six multi-dimensional scaling experiments were conducted: C4 not vocoded, C4 vocoded, B4 not vocoded, B4 vocoded, F5 not vocoded, and F5 vocoded. At the pitch C4, for both non-vocoded and vocoded conditions, dimension 1 grouped stimuli according to voice category and was most strongly predicted by spectral centroid from 0 to 2 kHz. While dimension 2 grouped stimuli according to excitation source spectral slope, it was organized slightly differently and predicted by different acoustic parameters in the non-vocoded and vocoded conditions. For pitches B4 and F5 spectral centroid from 0 to 2 kHz most strongly predicted dimension 1. However, while dimension 1 separated all 3 voice categories in the vocoded condition, dimension 1 only separated the soprano stimuli from the intermediate and mezzo-soprano stimuli in the non-vocoded condition. While it is unclear how these results predict timbre perception in CI listeners, in general, these results suggest that perhaps some aspects of vocal timbre may remain.

A pressing societal and scientific question is how social media use affects our cognitions, emotions, and behaviors. To answer this question, fine-grained insight into the content of individuals' social media use is needed. It is difficult to study content-based social media effects with traditional survey methods because such methods are incapable of capturing the extreme volume and variety of social media content that is shared and received. Therefore, this special issue aims to illustrate how content-based social media effects could be examined by integrating communication sciences and computational methods. We describe a three-step method to investigate content-based media effects, which involves (a) collecting digital trace data, (b) performing automated textual and visual content analysis, and (c) conducting linkage analysis. This Special Issue zooms in on these steps and describes the strengths and weaknesses of different computational methods. We conclude with some challenges that need to be addressed in future research. [ABSTRACT FROM AUTHOR]