The language of happiness in self-reported descriptions of happy moments: Words, concepts, and entities

Abstract

This article attempts to study the language of happiness from a double perspective. First, the impact and relevance of sentiment words and expressions in self-reported descriptions of happiness are examined. Second, the sources of happiness that are mentioned in such descriptions are identified. A large sample of “happy moments” from the HappyDB corpus is processed employing advanced text analytics techniques. The sentiment analysis results reveal that positive lexical items have a limited role in the description of happy moments. For the second objective, unsupervised machine learning algorithms are used to extract and cluster keywords and manually label the resulting semantic classes. Results indicate that these classes, linguistically materialized in compact lexical families, accurately describe the sources of happiness, a result that is reinforced by our named entities analysis, which also reveals the important role that commercial products and services play as a source of happiness. Thus, this study attempts to provide methodological underpinnings for the automatic processing of self-reported happy moments, and contributes to a better understanding of the linguistic expression of happiness, with interdisciplinary implications for fields such as affective content analysis, sentiment analysis, and cultural, social and behavioural studies.

Vanishing Boundaries: A Unifying Account of Multidimensional Emotion Dynamics and Alterations in Depression

“…To explore whether the emotional blunting in MDD extended to the reactivity to life events, we identified life events representing happy moments [26] in our dataset (detailed in the Methods section). Of note, prior research indicates that methods focused solely on classifying sentiments or emotions are inadequate for identifying expressions of happiness [27], as they can be conveyed in a variety of linguistic tones, not just positive ones [28]. "Happy moments" are expressions in natural language reflecting a subjective experience of joy, contentment, or satisfaction.…”

“…The HappyDB database [26] is an extensive collection of 100,000 happy moments gathered from more than 10,000 crowdsourcing workers. Given that happy moments reported by individuals are not always portrayed using positive words [28], and cannot be reliably detected using emotion detection models [27], the HappyDB corpus is a valuable resource for understanding the expressions of happiness in natural language. The corpus contains individuals' responses to the question "What made you happy in the past 24 hours", or in the last three months.…”

“…Learning to Extract Happy Moments with Positive Unlabeled Learning. While highly performant methods for sentiment and emotion detection from natural language have been developed [20,58,59], finding the expressions of happy moments in social media remains a challenging task [27,28]. We consider a happy moment to be a subjective experience characterized by feelings of joy, contentment, and satisfaction.…”

“…We consider a happy moment to be a subjective experience characterized by feelings of joy, contentment, and satisfaction. For conveying happy moments in textual data, individuals might rely on language with neutral or even negative sentiment [28]. Given that popular methods for emotion detection do not generalize for happy moments identification [27], and there is no dataset of positive and negative data for training a binary classifier for the task, we develop a deep learning classifier following the positive-unlabeled (PU) learning framework [57,60].…”

Neuroleadership: a new way for happiness management

“…In this context, organisations have faced the challenge of improving their management to adapt to the new times. The search for well-being has led to the application of concepts such as happiness management to create better workplaces (Cuesta-Valiño et al, 2022b;Moreno-Ortiz et al, 2022;Ravina-Ripoll et al, 2019a;. The leaders of companies have the role of making the necessary changes to make the workplaces happier and more productive.…”