Daily Happiness Research Articles

Redefining Snacking as a Piece of Daily Happiness: A Randomized Controlled Trial of Engagement in <i>Oyatsu</i> Activities for Improving Well-Being

Redefining Snacking as a Piece of Daily Happiness: A Randomized Controlled Trial of Engagement in <i>Oyatsu</i> Activities for Improving Well-Being

Happy but Not Happy The Correlation between Chinese High School Students' Grades and Their Level of Happiness

The purpose of this research is to address the growing attention on students mental health by examining how grades, which take up a huge portion of every student's daily life, can positively or negatively affect a student's happiness level. Many previous pieces of research on this topic adopted a very general perspective and focused on the global sample size. As a result, this study aims to concentrate exclusively on examining the correlation between grades and the daily happiness level of 39 Chinese high school students attending Shanghai Foreign Language High School. By drawing on reviews of similar studies before and distributing an online survey to participants through Wechat, the main Chinese communication platform, a curious phenomenon was identified. Despite reporting to be under great stress and suffering from occasional anxiety attacks, the participants reflected very positively on their daily mood and energy level, and I failed to identify a correlation due to the conflicting survey results. Future research should be conducted by further expanding on the sample size and investigating the special mental mechanism Chinese high school students potentially develop from their unique educational environment.

Twitter’s daily happiness sentiment, economic policy uncertainty, and stock index fluctuations

This research applies quantile Granger causality and impulse-response analyses to evaluate the causal linkages among Twitter’s daily happiness sentiment, economic policy uncertainty (EPU), and S&P 500 indices across the U.S. stock market cycles. We present notable evidence of bi-directional causality among cyclical components of Twitter’s daily happiness sentiment, economic policy uncertainty, and S&P 500 indices for most quantiles. The causal linkage of Twitter’s daily happiness sentiment and S&P 500 indices identified in this study reconciles the so-called Easterlin Paradox and Easterlin Illusion arguments from previous studies on income-happiness relationship. Moreover, given a high (low) EPU level, the positive (negative) impulse-response effects between the Twitter’s daily happiness sentiment and the S&P 500 indices are justified during a stock market bust cycle, but the signs of these correlations change to negative (positive) during a stock market boom cycle. These findings imply that investors’ hedging strategies can be linked to the surveillance of the Twitter’s daily happiness sentiment index.

Bidirectional associations between nightly sleep and daily happiness and negative mood in adolescents

This study examined bidirectional associations between daily happiness and negative mood and subjective and objective sleep measures. Participants were 311 adolescents (M age = 17.37 years; 51.8% female; 59.2% White/European American, 38.6% Black/African American, 1% Hispanic/Latinx American, 1.4% multi‐racial; 19.3% below poverty line) observed over a 7‐day period (2017–2018) using sleep diaries and actigraphy. Daily negative mood was related to greater subjective sleep/wake problems, and happiness was related to lower subjective sleep/wake problems. Conversely, shorter self‐reported sleep duration was related to higher negative mood the next day. For actigraphy measures, daily negative mood was related to greater sleep duration and efficiency, whereas happiness was related to lower sleep efficiency. Differences in associations based on subjective versus objective sleep measures are discussed.

The Relationship Between Prosociality, Meaning, and Happiness in Everyday Life

Prosocial behaviors benefit others, but what benefits do they hold for those who enact them? Prosociality can enhance the actor’s well-being, yet whether it is one’s sense of happiness or meaning that is impacted, and how this plays out in everyday life, has received limited attention. We address this gap in knowledge by examining how prosociality is related to daily meaning and happiness across two large daily diary studies in two countries. Study 1 (N = 1140) revealed that changes in one’s subjective sense of prosociality was uniquely associated with both daily meaning and happiness. Study 2 (N = 217) found that self-reported prosocial behavior was also clearly linked to increases in daily meaning, and modestly associated with daily happiness. Altogether, our findings suggest that the subjective sense of prosociality is associated with meaning and happiness, and that performing prosocial acts may be particularly relevant to experiencing meaning.

The relationship between global stock and precious metals under Covid-19 and happiness perspectives

In this paper, we examine the relationship between global stock markets, as respectively represented by the FTSE All-World Series and the MSCI Emerging Markets indexes, and the S&P GSCI Precious Metals index from 01 September 1999 to 03 May 2021. We employ the conditional correlation multivariate generalized autoregressive conditional heteroskedasticity (MGARCH) to investigate this stock-precious metals nexus in terms of return and volatility spillovers. The study assesses impacts of the Covid-19 pandemic on the stock-precious metals nexus and further examine this relationship by supplementing the Twitter’s Daily Happiness Sentiment index to the methodological framework for the period from 01 January 2020 to 03 May 2021. We find that precious metals positively influence stock markets before the Covid-19 outbreak and firmly play a valuable role due to their hedge and safe haven characteristics. In contrast, the bivariate GARCH framework does not provide statistically significant evidence on the stock-precious metals nexus during the Covid-19 pandemic. Meanwhile, the tri-variate GARCH approach with stock markets, precious metals, and happiness sentiment indexes reveals sufficiently complicated interactions between these return series. Prominently, past change in the happiness index negatively affects the stock returns but positively drives the performance of precious metals. These findings indirectly demonstrate the stock-precious metals nexus under impacts of the Covid-19 pandemic and reflect the demand of precious metals during crisis periods. Accordingly, we suggest a reasonable method of adjusting the proxies when no interaction effect is significantly found during unprecedented outbreaks.

The evolution of happiness pre and peri-COVID-19: A Markov Switching Dynamic Regression Model.

Happiness levels often fluctuate from one day to the next, and an exogenous shock such as a pandemic can likely disrupt pre-existing happiness dynamics. This paper fits a Marko Switching Dynamic Regression Model (MSDR) to better understand the dynamic patterns of happiness levels before and during a pandemic. The estimated parameters from the MSDR model include each state's mean and duration, volatility and transition probabilities. Once these parameters have been estimated, we use the one-step method to predict the unobserved states' evolution over time. This gives us unique insights into the evolution of happiness. Furthermore, as maximising happiness is a policy priority, we determine the factors that can contribute to the probability of increasing happiness levels. We empirically test these models using New Zealand's daily happiness data for May 2019 -November 2020. The results show that New Zealand seems to have two regimes, an unhappy and happy regime. In 2019 the happy regime dominated; thus, the probability of being unhappy in the next time period (day) occurred less frequently, whereas the opposite is true for 2020. The higher frequency of time periods with a probability of being unhappy in 2020 mostly correspond to pandemic events. Lastly, we find the factors positively and significantly related to the probability of being happy after lockdown to be jobseeker support payments and international travel. On the other hand, lack of mobility is significantly and negatively related to the probability of being happy.

Does happiness forecast implied volatility? Evidence from nonparametric wave-based Granger causality testing

Past studies on the causal relationship between online sentiment and implied volatility indices report mixed results. In this paper, we employ a daily happiness index extracted from Twitter as a proxy for online sentiment to investigate the relationship between sentiment and the Chicago Board of Option Exchange volatility indices. Applying a nonparametric wave-based Granger causality test, allows us close examination of frequencies and periods of causality. Investigating four different subsample periods, we evidence that daily happiness sentiment consistently manifests short-term causality of implied volatility indices. This is evidenced over our sample period as a whole, and for three out of four investigated subperiods—the exception being a subperiod of three years following the Global Financial Crisis. Additional Diebold and Yilmaz (2012) spillover testing evidences that the causal relationship between happiness and implied volatility is strongest for stable low happiness subperiods. Importantly, we also evidence intervals where spillovers from happiness to implied volatility spike sharply. This suggests that the relationship between happiness and implied volatility is heavily conditioned by exogenous factors. Consequently, while we identify consistent short-term causality of happiness to implied volatility measures, economically meaningful forecasting of implied volatility from happiness remains elusive. Our findings should be of considerable interest to investors and practitioners, as well as to behavioral finance researchers interested in how sentiment shapes the ‘uncertainty of uncertainty.

The relationship between global wealth and happiness: An analytical study of returns and volatility spillovers

This paper explores the relationship between global wealth and happiness. We employ a bivariate generalized autoregressive conditional heteroskedasticity framework for global wealth and happiness represented, respectively, by FTSE All-World and Twitter's Daily Happiness Sentiment indexes from October 14, 2013 to December 31, 2019. We find that daily changes in happiness significantly mitigate wealth volatility, and daily wealth returns positively affect the changes in happiness sentiment. These findings reveal a spiral transmission in daily changes in happiness sentiment and global wealth volatility and returns. Metaphysically, our findings imply that the relationship between the mind and matter of finance is either materialist or monistically neutral. From alternative perspective, we construct a pseudo portfolio of global wealth and happiness indexes in which the factor of happiness plays a more important role. Thus, a concentration on happiness is preferable for the pursuit of multiple objectives, which essentially include mind and matter.

Outliers in Smartphone Sensor Data Reveal Outliers in Daily Happiness

Enabling smartphones to understand our emotional well-being provides the potential to create personalised applications and highly responsive interfaces. However, this is by no means a trivial task - subjectivity in reporting emotions impacts the reliability of ground-truth information whereas smartphones, unlike specialised wearables, have limited sensing capabilities. In this paper, we propose a new approach that advances emotional state prediction by extracting outlier-based features and by mitigating the subjectivity in capturing ground-truth information. We utilised this approach in a distinctive and challenging use case - happiness detection - and we demonstrated prediction performance improvements of up to 13% in AUC and 27% in F-score compared to the traditional modelling approaches. The results indicate that extreme values (i.e. outliers) of sensor readings mirror extreme values in the reported happiness levels. Furthermore, we showed that this approach is more robust in replicating the prediction model in completely new experimental settings.

Improving well-being and behavior in adolescents utilizing a school-based positive psychology intervention

ABSTRACT This study is a multi-component Positive Psychology Intervention (PPI) with the goal of improving daily happiness and classroom behavior in a sample at-risk high-school students. PPIs have increasingly been used in school settings to enhance student well-being, student success, and to increase positive affect. The current study utilized a multiple baseline design, across five adolescents, to examine whether a manualized PPI implemented in individual school-based counseling sessions with at-risk high-school students, would lead to increased happiness, improved classroom behavior, and life satisfaction, measured through a Daily Happiness survey, the Direct Behavior Rating (DBR), General Happiness Scale, Brief Multidimensional Students’ Life Satisfaction Scale, and the Student Life Satisfaction Scale. Results demonstrated high variability in the data and an overall null effect of the intervention on the two dependent variables of daily happiness and classroom behavior. Limitations included individual impacts of outside factors on student reports and behavior. Due to the small scale of the study and lack of observed intervention effects, more research is needed to draw conclusions about the application of the intervention. However, social validity data revealed that school-based mental health professionals may still consider this intervention to teach students strategies to improve life satisfaction.

Dynamic Cross-Correlation between Online Sentiment and Stock Market Performance: A Global View

This paper focuses on investigating the dynamic cross-correlation relationship between online sentiment and returns of major global stock markets based on the MF-DCCA method. We use Daily Happiness (DHS), an index derived from Twitter posts through textual analysis as a proxy of online sentiment. By dividing the global financial markets into developed and developing ones, we are able to test the heterogeneous relationship between stock market performance and sentiment at different economic developing level. Empirical results show that there exists a power-law cross-correlation relationship between financial market and online sentiment in some developed countries and all developing countries, and the relationship is more stable in the developing countries. Moreover, we apply rolling window analysis to capture the dynamic evolution characteristics and find the relationship has a strong consistency over time. Our work provides a much more delicate perspective to test the relationship between online sentiment and financial markets performance and enriches the existing literature.

Increased Social Interactions Reduce the Association Between Constricted Life-Space and Lower Daily Happiness in Older Adults With and Without HIV: A GPS and Ecological Momentary Assessment Study

Older persons with human immunodeficiency virus (HIV) (PWH) are particularly susceptible to life-space restrictions. The aims of this study included: 1) using global positioning system (GPS) derived indicators as an assessment of time spent at home among older adults with and without HIV; 2) using ecological momentary assessment (EMA) to examine real-time relationships between life-space, mood (happiness, sadness, anxious), fatigue, and pain; and 3) determining if number of daily social interactions moderated the effect of life-space on mood. Eighty-eight older adults (PWH n = 54, HIV-negative n = 34) completed smartphone-based EMA surveys assessing mood, fatigue, pain, and social interactions four times per day for two weeks. Participants' smartphones were GPS enabled throughout the study. Mixed-effects regression models analyzed concurrent and lagged associations among life-space and behavioral indicators of health. PWH spent more of their time at home (79% versus 70%, z = -2.08; p = 0.04) and reported lower mean happiness (3.2 versus 3.7; z = 2.63; p = 0.007) compared to HIV-negative participants. Controlling for covariates, more daily social interactions were associated with higher ratings of real-time happiness (b = 0.12; t = 5.61; df = 1087.9; p< 0.001). Similar findings were seen in lagged analyses: prior day social interactions (b = 0.15; t = 7.3; df = 1024.9; p < 0.0001) and HIV status (b = -0.48; t = -2.56; df = 1026.8; p = 0.01) attenuated the effect of prior day time spent at home on happiness. Accounting for engagement in social interactions reduced the significant effect of time spent at home and lower happiness. Interventions targeting social isolation within the context of constricted life-space may be beneficial for increasing positive mood in older adults, and especially relevant to older PWH.

Quantifying the cross sectional relation of daily happiness sentiment and return skewness: Evidence from US industries

In this paper, we initiate cross-sectional return skewness correlation study between investor daily happiness sentiment (DHS) and twenty-two US industry indices. The Twitter happiness index, originated from the world’s largest microblog platform, Twitter.com, is employed as the representative of DHS. Also, with quantile setting of DHS, we break our full sample into five subsamples and detect apparent and reliable skewness distinctions among DHS subgroups. We further implement the robustness check with altered subgroups for the credibility enhancement. In summary, the robustness results follow the steps of original findings.

청소년의 일상생활과 행복 간의 관계: 빈곤과 비빈곤 청소년의 비교

청소년의 일상생활과 행복 간의 관계: 빈곤과 비빈곤 청소년의 비교

Quantifying the cross sectional relation of daily happiness sentiment and stock return: Evidence from US

In this paper, we utilize the natural log value of Twitter happiness index as the measurement for investor daily happiness sentiment (DHS) and investigate its cross-sectional correlations with twelve US indices. With correlation coefficients and Granger causality tests, we find contemporaneous and long-term interactions between DHS and indices returns. In addition, we discover noticeable return differences across quantile subgroups and the differences are further qualified with significant statistics. We also carry out another robustness check with altered quantile setting. In general, the robustness results show no divergence with prior empirical findings.

Prediction of Daily Happiness Using Supervised Learning of Multimodal Lifelog Data

Developing an approach to predict happiness based on individual conditions and actions could enable us to select daily behaviors for enhancing well-being in life. Therefore, we propose a novel approach of applying machine learning, a branch of the field of artificial intelligence, to a variety of information concerning people’s lives (i.e., a lifelog). We asked a participant (a healthy young man) to record 55 lifelog items (e.g., positive mood, negative events, sleep time etc.) in his daily life for about eight months using smartphone apps and a smartwatch. We then constructed a predictor to estimate the degree of happiness from the multimodal lifelog data using a support vector machine, which achieved 82.6% prediction accuracy. This suggests that our approach can predict the behaviors that increase individuals’ happiness in their daily lives, thereby contributing to improvement in their happiness. Future studies examining the usability and clinical applicability of this approach would benefit from a larger and more diverse sample size.

Quantifying the correlation and prediction of daily happiness sentiment and stock return: The Case of Singapore

In this paper, with the newly emerged Twitter happiness index, we employ the VAR regression, linear, and nonlinear Granger causality tests to investigate the predictive correlations between daily happiness sentiment (DHS) and Singapore Straits Times Index (STI) stock performance indicators. The empirical results reveal that DHS presents significant predictability with future STI return. While, for the realized volatility, no compelling forecasting powers are detected. We also perform another two subsample tests as robustness checks. In general, the subsample results are in line with those of the full sample.

Relations between Reactive and Proactive Aggression and Daily Emotions in Adolescents.

The current study examined whether individual differences in reactive and proactive aggression: 1) relate to level of daily emotion, including happiness, sadness, anger, and fear, 2) predict across-day variability in these emotions, and 3) moderate reactivity of these emotions to positive and negative events. Participants were a racially/ethnically diverse sample of 144 adolescents (80 girls, 64 boys; M age = 13.55years; SD = 1.34). Adolescents self-reported on reactive and proactive aggression in a home visit prior to the collection of daily data. Using daily dairy procedures, adolescents then reported on their daily emotions and positive/negative events over 12 consecutive days. Higher reactive aggression was associated with greater levels of daily anger, more variability in anger across days, and heightened angry reactivity to negative events. Additionally, higher reactive aggression predicted lower levels of daily happiness but greater happy reactivity to positive events. Finally, higher reactive aggression was linked to increased variability in daily fear. In contrast, proactive aggression was largely unrelated to adolescents' daily emotions, with the exception that higher proactive aggression predicted less variability in happiness across days. Results indicate that reactive aggression is characterized by significant emotionality at the daily level, and proactive aggression is characterized by lack of emotionality.

Emotional Coregulation in Mexican-Origin Parent-Adolescent Dyads: Associations with Adolescent Mental Health.

Research on the health benefits and consequences of close relationships has suggested the linkage in daily emotions (i.e., coregulation) between close partners is an important relationship dynamic. While the coupling of daily emotions among family members (parent-child and marital dyads) has been widely documented, research examining emotional coregulation among ethnic minority youth during adolescence, a period marked by heightened emotion and risk for psychopathology, remains an important area in need of exploration. This study examined correlates of emotional coregulation in a sample of Mexican-origin adolescents (Mage = 15.02, SD = .83) and their parents (Mage = 41.93, SD = 6.70). Dyads reported on daily levels of distress and happiness for 14 consecutive days across two waves of data collection a year apart (nwave1 = 428 dyads, nwave2 = 336 dyads). Dyads who reported getting along were more likely to coregulate their daily happiness. Importantly, coregulation of distress was only present in older adolescents who reported above average levels of internalizing symptoms. The results suggest coregulation of distress may shape or be shaped by poor mental health during the later years of adolescence, a time when youth may be establishing a degree of emotional autonomy from parents.