Stay Home, Drink at Home? A Daily Diary Study on College Students' Alcohol and Social Media Use during the COVID-19 Pandemic.

BACKGROUND: COVID-19 and measures to contain it may have impacted college students' behavior, including their drinking behavior. Students' drinking may have decreased-for example, due to the closure of bars-but problematic drinking may have increased-for example, due to (solitary) drinking at home. Another behavior that has increased due to COVID-19 and the accompanying social isolation is students' social networking site (SNS) use. This is worrisome because students' SNS use has been shown to increase their alcohol use. Nevertheless, little research has investigated these behaviors and the possible link between them during a lockdown. Therefore, this study aimed to examine (1) whether students engaged in drinking during a lockdown, (2) whether they displayed their drinking behavior on SNSs, and (3) whether exposure to and posting of alcohol-related content was linked to their daily alcohol use. METHODS: 337 college students (Mage = 20.63 years, SDage = 1.55 years; 50.3% male) participated in a two-week daily diary study. Descriptive statistical analyses and generalized linear mixed modeling (GLMM) were deployed. RESULTS: Descriptive analysis results showed that during the week, students' drinking occurred with friends in dormitories, while in the weekend, this behavior shifted to drinking with friends and parents at home. Moreover, students mostly saw visual and posted textual posts of this drinking on SNSs. Furthermore, GLMM revealed associations between exposure to alcohol postings, sharing of alcohol postings, and students' probability of drinking on the same day. CONCLUSION: This study provides important insights into students' alcohol use and its underlying mechanisms during health crises.

#Coronavirus: Monitoring the Belgian Twitter Discourse on the Severe Acute Respiratory Syndrome Coronavirus 2 Pandemic.

In this study, a social media analysis is conducted to examine the public discourse about the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) pandemic on Twitter. In particular, this study aims to examine (a) how the number of tweets varies as a function of the timeline of the pandemic and associated measures and (b) how the content of these tweets, including displayed emotions, changes. Therefore, 373,908 tweets and retweets from Belgium were collected from February 25, 2020 to the March 30. Time series analysis, network bigrams, topic models, and emotional lexica were deployed for analysis. The results showed that significant events related to the virus correlated with an immediate increase in the number of tweets addressing them. Furthermore, the Belgian Twitter discourse was characterized by positively connoted words, which also refer to European solidarity. These findings do not only stress the relevance of Twitter as a medium for public discourse during lockdowns, but also seem to indicate that the Belgian public supports policy measures that respect solidarity in Europe.

Mothers Matter: Using Regression Tree Algorithms to Predict Adolescents' Sharing of Drunk References on Social Media.

Exposure to online drinking on social media is associated with real-life alcohol consumption. Building on the Theory of planned behavior, the current study substantially adds to this line of research by identifying the predictors of sharing drunk references on social media. Based on a cross-sectional survey among 1639 adolescents with a mean age of 15 (59% female), this study compares and discusses multiple regression tree algorithms predicting the sharing of drunk references. More specifically, this paper compares the accuracy of classification and regression tree, bagging, random forest and extreme gradient boosting algorithms. The analysis indicates that four concepts are central to predicting adolescents' sharing of drunk references: (1) exposure to them on social media; (2) the perceived injunctive norms of the mother towards alcohol consumption; (3) the perceived descriptive norms of best friends towards alcohol consumption; and (4) willingness to drink alcohol. The most accurate results were obtained using extreme gradient boosting. This study provides theoretical, practical, and methodological conclusions. It shows that maternal norms toward alcohol consumption are a central predictor for sharing drunk references. Therefore, future media literacy interventions should take an ecological perspective. In addition, this analysis indicates that regression trees are an advantageous method in youth research, combining accurate predictions with straightforward interpretations.