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Building on recent findings by Fournier and colleagues (2023), the present study examined the fit of a bi-dimensional model of problematic Instagram use, distinguishing between non-pathological high engagement and problematic symptoms mirroring addictive tendencies. A sample of 696 Italian adults completed an online survey assessing problematic Instagram use, personality traits, psychological distress, usage motives for Instagram use, and Instagram usage metrics. Confirmatory factor analysis supported the bi-dimensional model, with high engagement (salience and tolerance) and problematic symptoms (relapse, withdrawal, conflict, and mood modification) as distinct factors. Neuroticism, depression, emotional dysregulation, loneliness, and FoMO and the diversion motive were more strongly correlated with problematic symptoms. In turn, social interaction, documentation, and self-promotion were more associated with high engagement. Frequency of sharing posts and stories were also more strongly correlated with high engagement. These findings highlight the importance of distinguishing between high engagement and addiction-like symptoms in understanding problematic Instagram use and inform the development of targeted interventions.

The present study investigated the postdictive validity of self-report Big Five personality traits using over ten years of recording of online behaviors, namely Facebook Page Likes. We explored how personality traits correlate with interests and preferences expressed through Facebook Likes recorded up to ten years before the personality assessment and examined the consistency of these correlations over time. The recruited sample consisted of 601 adult Facebook users, predominantly young adults, with 73.70 % female and 26.30 % male participants. Facebook Page Likes data were analyzed using topic modeling techniques to extract meaningful indicators of individual difference in user interests. Findings revealed significant associations between personality traits and participants' interests as expressed using Likes over ten years of online activity. Conscientiousness showed consistent negative correlations with leisure and entertainment interests. Openness to Experience positively correlated with interests in artistic and cultural fields, including non-profit organizations, theaters, musicians, and entertainment and media. Extraversion demonstrated positive correlations with social entertainment, such as nightclubs and restaurants. Agreeableness and Emotional Stability did not show significant average associations. There was a negative correlation between the number of Likes and Conscientiousness, suggesting that individuals that are more conscientious express fewer Page Likes. Conversely, a positive correlation existed between Page Likes and Openness. Overall, correlations were small but mostly consistent over time, although correlations with the Openness trait suggested a stronger association with more recent interests. This research underscores the enduring influence of personality on online behaviors, including activity on social media.

Introduction This study aims to explore the relationship between cyberbullying involvement either as a perpetrator or a victim and emotional responses to virtual social exclusion and inclusion. Previous research has predominantly focused on the impacts of in-person bullying. Our study shifts this focus to the cyber realm. Methods A total of 156 adolescents living in northern Italy were recruited ( M age : 12.26; SD = 0.87; 43% female). After completing measures of empathy and involvement in cyberbullying, adolescents participated in the cyberball tasks. Latent profile analysis was used to identify subgroups. Results We found three groups: Class 3, reporting negative responses to the social exclusion tasks and positive responses to the social inclusion tasks; Class 1, reporting neutral emotional responses to social inclusion and negative emotional responses to social exclusion; and Class 2, showing neutral responses to ‘social exclusion’ tasks and strongly positive responses to ‘social inclusion’ tasks. Linear regression revealed that cyberbullies report a typical emotional response to exclusion and inclusion tasks (Class 3), whereas cybervictims are more likely to report negative responses to both exclusion and inclusion events (Class 1). High levels of empathy are associated with the manifestation of a typical emotional response (Class 3), in contrast to an impaired emotional response characterized by neutral or positive responses to conditions of ‘social exclusion’ and positive responses to conditions of ‘social inclusion’ (Class 2). Conclusion Results underscore the complex interplay between cyberbullying roles and emotional responses to virtual social experiences. Theoretical implications and limitations of the research are discussed.

The present study explored how sharing verbal status updates on Facebook and receiving Likes, as a form of positive social feedback, correlate with current and perceived changes in Quality of Life (QoL). Utilizing the Facebook Graph API, we collected a longitudinal dataset comprising status updates and Likes received by 1577 adult Facebook users over a 12-month period. Two monthly indicators were calculated: the percentage of verbal status updates and the average number of Likes per post. Participants were administered a survey to assess current and perceived changes in QoL. Confirmatory Factor Analysis (CFA) and the Auto-Regressive Latent Trajectory Model with Structured Residuals (ALT-SRs) were used to model longitudinal patterns emerging from the objective recordings of Facebook activity and explore their correlation with QoL measures. Findings indicated a positive correlation between the percentage of verbal status updated on Facebook and current QoL. Online positive social feedback, measured through received Likes, was associated with both current QoL and perceived improvements in QoL. Of note, perceived improvements in QoL correlated with an increase in received Likes over time. Results highlight the relevance of collecting and modeling longitudinal Facebook data for the investigation of the association between activity on social media and individual well-being.

Abstract The Affective Neuroscience Personality Scales (ANPS) were constructed as a self-report assessment to measure individual differences in Jaak Panksepp’s cross-species primary emotional systems: SEEKING, PLAY, CARE (positive emotions) and FEAR, SADNESS, ANGER (negative emotions). Beginning with the first published work on the ANPS in 2003, individual differences on the ANPS measures of these six primary emotional systems have been consistently linked to Big Five personality traits. From a theoretical perspective, these primary emotional systems arising from subcortical regions, shed light on the nature of the Big Five personality traits from an evolutionary perspective, because each of these primary emotional systems represent a tool for survival endowing mammalian species with inherited behavioral programs to react appropriately to complex environments. The present work revisited 21 available samples where both ANPS and Big Five measures have been administered. Our meta-analytical analysis provides solid evidence that high SEEKING relates to high Openness to Experience, high PLAY to high Extraversion, high CARE/low ANGER to high Agreeableness and high FEAR/SADNESS/ANGER to high Neuroticism. This seems to be true regardless of the ANPS inventory chosen, although much more work is needed in this area. Associations between primary emotional systems and Conscientiousness were in the lower effect size area across all six primary emotions, thereby supporting the idea that Conscientiousness rather seems to be less directly related with the subcortical primary emotions and likely is the most cognitive/cortical personality construct out of the Big Five. In sum, the present work underlines the idea that individual differences in primary emotional systems represent evolutionarily ancient foundations of human personality, given their a) meaningful links to the prominent Big Five model and b) their origins lying in subcortical areas of the human brain.

Bullying continues to be a social issue affecting millions of students of all ages worldwide. Research on bullying seems to be dominated by quantitative research approaches employed standardized categories and measures, ultimately limiting our knowledge about children’s own view on bullying. Our research follows another direction, aiming to explore the representation of bullying in a sample of Italian primary school children by using and comparing the functioning of two qualitative research instruments: interviews, and children’s drawings. In addition, aided by quantitative analyses, we aimed to investigate whether students’ involvement in different bullying roles (as bullies, victims, or defenders), as measured by self-assessment, correlated with different characteristics of the representation of bullying emerging from children’s drawings and interviews. We recruited a convenient sample of 640 primary school students (mean age = 9.44; SD = 0.67), 53.3% of whom were male. The results showed that all forms of bullying, i.e., physical, verbal, and social bullying, could be identified in interview and drawing data, although references to all types of bullying were more frequent in interview data. In terms of bullying criteria, the presence of a power imbalance between the bully and the victim was most frequently detected in both the interview data and the drawing data, while repetition was more easily detected in the interview data. The interview data showed that sadness was the most frequently reported victim emotions, followed by fear, anger, and lack of emotion. The drawing data showed a similar pattern, although victims were more frequently described as lacking emotions compared to the interview data. In both interview and drawing data, age and female gender were positively associated with references to verbal bullying, and negatively associated with references to physical bullying. Additionally, bully/victim children were more likely than uninvolved children to depict physical bullying in the drawings, while this association was not detected in interview data. In summary, our study shows that, compared with drawings, interviews tend to provide a more comprehensive view of children’s own representation of bullying, while drawing data tend to show stronger connections with children’s current personal experiences of bullying.

We retrieved the current profile picture of 2234 Italian Facebook users who also answered self-report questionnaires on demographic variables and personality. Data were collected between March and June 2018 using a Facebook web application. Profile pictures consisting of 200 × 200 resolution jpegs were obtained by sending a request via the Facebook Graph API and analyzed using online commercial services allowing for the scoring of facial expressions in image data, namely Microsoft Azure Face API and MEGVII Face++ Detect API. Both services provide emotional expression scores if at least one face is successfully detected in the picture. Using the Microsoft Azure Face API we obtained scores for anger, contempt, disgust, fear, joy, sadness, surprise, and neutrality. Using the MEGVII Face++ Detect API, pictures were scored for the presence of anger, disgust, fear, joy, sadness, and surprise, and neutrality. Higher scores on each emotion refer to a stronger expression of the respective emotion. The dataset presented here consists of data of N =728 Facebook users with a profile picture in which both APIs detected only one face. Regarding self-report data, the dataset includes the following demographic information about the participants: gender and age. The dataset also includes participants’ personality scores based on a short validated assessment of Big Five traits (Ten Item Personality Inventory), and Impulsivity/Sensation Seeking (IMPSS8). A document including the questions administered in the online survey is attached to the dataset. This dataset can be useful to generate insights on the association between demographic variables, including age and gender, and personality (Big Five traits and Impulsivity/Sensation Seeking), and emotional expression as derived from social media pictures. It can be useful for researchers and data scientists who do research in social sciences, in particular psychoinformatics, to train models in order to infer personality of users of social media platforms from profile pictures.

More than three billion users are currently on one of Meta’s online platforms with Facebook being still their most prominent social media service. It is well known that Facebook has designed a highly immersive social media service with the aim to prolong online time of its users, as this results in more digital footprints to be studied and monetized (via psychological targeting). In this context, it is debated if social media platforms can elicit addictive behaviors. In the present work, we demonstrate in N = 1,094 users that it is possible to predict from digital footprints of the Facebook users their self-reported addictive tendencies toward social media (R > 0.30) by applying machine-learning strategies. More specifically, we analyzed the predictive power of a set of models based on different sets of features extracted from digital traces, namely posting activity, language use, and page Likes. To maximize the predictive power of the models, we used an ensemble of linear and non-linear prediction algorithms. This work showed also sufficient accuracy rates (AUC above 0.70) in distinguishing between disordered and non-disordered social media users. In sum, individual differences in tendencies toward “social networks use disorder” can be inferred from digital traces left on the social media platform Facebook. Please note that the present work is limited by its cross-sectional design.

BackgroundSocial communication via instant messaging (IM) and social networking (SN) apps makes up a large part of the time that smartphone users spend on their devices. Previous research has indicated that the excessive use of these apps is positively associated with problematic smartphone use behaviors. In particular, image-based SN apps, such as Instagram (Facebook Inc) and Snapchat (Snap Inc), have been shown to exert stronger detrimental effects than those exerted by traditional apps, such as Facebook (Facebook Inc) and Twitter (Twitter Inc). ObjectiveIn this study, we investigated the correlation between individuals’ tendencies toward smartphone use disorder (SmUD) and objective measures of the frequency of smartphone usage. Additionally, we put to test the hypothesis that the pathway linking the frequency of actual smartphone usage to self-reported tendencies toward SmUD was mediated by the increased frequency of IM and SN app usage. MethodsWe recruited a sample of 124 adult smartphone users (females: 78/124, 62.9%; age: mean 23.84 years, SD 8.29 years) and collected objective information about the frequency of smartphone and SN app usage over 1 week. Participants also filled in a self-report measure for assessing the multiple components of tendencies toward SmUD. Bivariate associations were investigated by using Spearman correlation analyses. A parallel mediation analysis was conducted via multiple regression analysis. ResultsThe frequency of smartphone usage, as well as the use of IM apps (Messenger, Telegram, and WhatsApp [Facebook Inc]), Facebook, and image-based apps (Instagram and Snapchat), had significant positive associations with at least 1 component of SmUD, and the cyberspace-oriented relationships factor exhibited the strongest associations overall. We found support for an indirect effect that linked actual smartphone usage to SmUD tendencies via the frequency of the use of image-based SN apps. ConclusionsOur novel results shed light on the factors that promote SmUD tendencies and essentially indicate that image-based SN apps seem to be more strongly associated with problematic smartphone behaviors compared to IM apps and traditional SN apps, such as Facebook.

Currently, 2.7 billion people use at least one of the Facebook-owned social media platforms – Facebook, WhatsApp, and Instagram. Previous research investigating individual differences between users and non-users of these platforms has typically focused on one platform. However, individuals typically use a combination of Facebook-owned platforms. Therefore, we aim (1) to identify the relative prevalence of different patterns of social media use, and (2) to evaluate potential between-group differences in the distributions of age, gender, education, and Big Five personality traits. Data collection was performed using a cross-sectional design. Specifically, we administered a survey assessing participants’ demographic variables, current use of Facebook-owned platforms, and Big Five personality traits. In N = 3003 participants from the general population (60.67% females; mean age = 35.53 years, SD = 13.53), WhatsApp emerged as the most widely used application in the sample, and hence, has the strongest reach. A pattern consisting of a combined use of WhatsApp and Instagram appeared to be most prevalent among the youngest participants. Further, individuals using at least one social media platform were generally younger, more often female, and more extraverted than non-users. Small differences in Conscientiousness and Neuroticism also emerged across groups reporting different combinations of social media use. Interestingly, when examined as control variables, we found demographic characteristics partially accounted for differences in broad personality factors and facets across different patterns of social media use. Our findings are relevant to researchers carrying out their studies via social media platforms, as sample characteristics appear to be different depending on the platform used.

Recent literature suggests that variations in both formal and content aspects of texts shared on social media tend to reflect user-level differences in demographic, psychosocial, and behavioral characteristics. In the present study, we examined associations between language use on Facebook and problematic alcohol use. We collected texts shared on Facebook by a sample of 296 adult social media users (66.9% females; mean age = 28.44 years (SD = 7.38)). Texts were mined using the closed-vocabulary approach based on the Linguistic Inquiry Word Count (LIWC) semantic dictionary, and an open-vocabulary approach performed via Latent Dirichlet Allocation (LDA). Then, we examined associations between emerging textual features and alcohol-drinking scores as assessed using the AUDIT-C questionnaire. As a final aim, we employed the Random Forest machine-learning algorithm to determine and compare the predictive accuracy of closed- and open-vocabulary features over users' AUDIT-C scores. We found use of words about family, school, and positive feelings and emotions to be negatively associated with alcohol use and problematic drinking, while words suggesting interest in sport events, politics and economics, nightlife, and use of coarse language were more frequent among problematic drinkers. Results coming from LIWC and LDA analyses were quite similar, but LDA added information that could not be retrieved only with LIWC analysis. Furthermore, open-vocabulary features outperformed closed-vocabulary features in terms of predictive power over participants’ AUDIT-C scores (r = .46 vs. r = .28, respectively). Emerging relationships between text features and offline behaviors may have important implications for alcohol screening purposes in the online environment.

School transitions require students to adapt to new challenges and situations and can increase the risk of externalizing and internalizing psychological symptoms. The teacher-student relationship seems to be a protective factor for the risk of developing psychological symptoms during school transitions. The aim of the present study is to investigate whether the quality of the teacher-student relationship predicts the decrease of internalizing and externalizing symptoms during three school transitions, namely: from kindergarten to primary school (T1), from primary to middle school (T2), and from middle to high school (T3). We recruited 127 kindergarten students (mean age = 5.40, SD = 0.49), 113 fifth grade primary school students (mean age = 10.64, SD = 0.54), and 240 eighth grade students (mean age = 13.88, SD = 0.37) and their teachers (response rate = 95%). Data were collected from 2016 to 2018. Teachers filled out an anonymous survey, acting as informants for the students, reporting demographic details (age, gender), psychological symptoms, and quality of the teacher-student relationship. The data show that a positive teacher-student relationship quality tends to be associated with a reduction of psychological symptoms. A stable, low-conflict teacher-student relationship was confirmed as a protective factor from increased internalizing and externalizing symptoms during all normative school transitions. Furthermore, we see that an increase in teacher-student conflict during the transitions from primary to middle school, and from middle to high school is linked to an exacerbation in students’ externalizing symptoms during the first year of attendance of the new school. Our study confirms the importance of the teacher-student relationship in reducing psychological symptoms associated with school transitions, in every type of transition, favoring an improved psychological adjustment to the new environment. A positive teacher-student relationship represents a protective factor for the development of students. Study limitations are discussed.

In adolescence, bullying victimization is typically represented in terms of a three-fold factor structure reflecting three components of verbal, physical, and social victimization. Recent studies have suggested the usefulness of alternativte models including both general and component-specific factors. In this study, we assessed the empirical and theoretical validity of an instrument assessing verbal, physical and social victimization using a set of alternative models of victimization: a unidimensional model, a three-factor model, and a bifactor model. Association between emerging factors and student variables were explored to establish theoretical fit of the models. Sample consisted of upper primary and lower secondary school students [N = 1311; 53% Male; Mean age (SD) = 10.73 (1.45)] and their teachers. The three factor and bifactor models showed good fit. In spite of acceptable fit, the unidimensional model showed lower empirical support when compared with the other models. The dimensions of the three-factor model showed similar associations with most student variables, while the bifactor showed more heterogeneous, and theoretically coherent associations. General victimization decreased with age and was positively related with externalizing and internalizing symptoms, student–teacher conflict and negative expectations. Verbal victimization showed increased prevalence among girls and older students. Physical victimization showed increased prevalence among boys and younger students, and positive associations with externalizing symptoms and student–teacher conflict. Social victimization was more frequent among girls, and positively related with internalizing symptoms and negative expectations toward teachers. These findings highlight the usefulness of modeling victimization using both general and form-specific dimensions for both assessment and theory-building purposes.

When there is an interest in tracking longitudinal trends of student educational achievement using standardized tests, the most common linking approach generally involves the inclusion of a common set of items across adjacent test administrations. However, this approach may not be feasible in the context of high-stakes testing due to undesirable exposure of administered items. In this paper, we propose an alternative design, which allows for the equating of multiple operational tests with no items in common based on the inclusion of common items in an anchor test administered in a post-test condition. We tested this approach using data from the assessment program implemented in Italy by the National Institute for the Educational Evaluation of Instruction and Training for the years 2010–2012, and from a convenience sample of 832 8th grade students. Additionally, we investigated the impact on functioning of common items of varying item position and orders across test forms. Linking of tests was performed using multiple-group Item Response Theory modeling. Results of linking indicated that operational tests showed little variation in difficulty over the years. Investigation of item position and order effects showed that changes in item position closer to the end of the test, as well as the positioning of difficult items at the beginning or in the middle section of a test lead to a significant increase in difficulty of common items. Overall, findings indicate that this approach represents a viable linking design, which can be useful when the inclusion of common items across operational tests is not possible. The impact of differential item functioning of common items on equating error and the ability to detect ability trends is discussed.

Our study adopted a person-based approach with the aim to identify socio-behavioral profiles of primary school students based on peer group perception. The study involved 109 classes and their teachers, from the first three grades of elementary school. The final student sample consisted of 424 children, aged 6–9 years (M = 94.9 months; SD = 9.7), of whom 58.3% were male. We used peer-group nomination to investigate the aspects that are linked to peer group acceptance and perception of classroom behaviors, with reference to academic and relational criteria. We identified and defined six clusters. We validated these clusters by taking into consideration the children’s academic performances and the teacher’s perceptions of their relationship with the single students. The identified clusters were related to both of these aspects, and they show predictive value when referring to children’s behaviors as evaluated by their teachers. Implications for theory and educational policies are discussed.