This paper explores the relationship between social capital and happiness both in Europe as a whole, as well as in its four main geographical macro-regions – North, South, East and West – separately. We test the hypothesis of whether social capital, in its three-fold definition established by Coleman (1988) – trust, social interaction, and norms and sanctions – influences individual happiness across European countries and regions. The concept of social capital is further enriched by incorporating Putnam- (1993) and Olson- (1982) type variables on associational activity. Using ordinal logistic regression analysis on data for 48,583 individuals from 25 European countries, we reach three main findings. First, social capital matters for happiness across the three dimensions considered. Second, the main drivers of the effects of social capital on happiness appear to be informal social interaction and general social, as well as institutional trust. And third, there are significant differences in how social capital interacts with happiness across different areas of Europe, with the connection being at is weakest in the Nordic countries.

Social Capital and Individual Happiness in Europe

Many topics that scientists investigate speak to people's ideological worldviews. We report three studies-including an analysis of large-scale survey data-in which we systematically investigate the ideological antecedents of general faith in science and willingness to support science, as well as of science skepticism of climate change, vaccination, and genetic modification (GM). The main predictors are religiosity and political orientation, morality, and science understanding. Overall, science understanding is associated with vaccine and GM food acceptance, but not climate change acceptance. Importantly, different ideological predictors are related to the acceptance of different scientific findings. Political conservatism best predicts climate change skepticism. Religiosity, alongside moral purity concerns, best predicts vaccination skepticism. GM food skepticism is not fueled by religious or political ideology. Finally, religious conservatives consistently display a low faith in science and an unwillingness to support science. Thus, science acceptance and rejection have different ideological roots, depending on the topic of investigation.

https://journals.sagepub.com/doi/pdf/10.1177/0146167217741314

Not All Skepticism Is Equal: Exploring the Ideological Antecedents of Science Acceptance and Rejection:

Comunicacio presentada al 12th International Workshop on Semantic Evaluation (SemEval-2018), celebrat els dies 5 i 6 de juny de 2018 a Nova Orleans, EUA.

/pdf/semeval-2018-task-2-multilingual-emoji-prediction-1qt668ff9o.pdf

SemEval 2018 Task 2: multilingual emoji prediction

The increasing popularity of social media platforms such as Twitter and Facebook has led to a rise in the presence of hate and aggressive speech on these platforms. Despite the number of approaches recently proposed in the Natural Language Processing research area for detecting these forms of abusive language, the issue of identifying hate speech at scale is still an unsolved problem. In this article, we propose a robust neural architecture that is shown to perform in a satisfactory way across different languages; namely, English, Italian, and German. We address an extensive analysis of the obtained experimental results over the three languages to gain a better understanding of the contribution of the different components employed in the system, both from the architecture point of view (i.e., Long Short Term Memory, Gated Recurrent Unit, and bidirectional Long Short Term Memory) and from the feature selection point of view (i.e., ngrams, social network–specific features, emotion lexica, emojis, word embeddings). To address such in-depth analysis, we use three freely available datasets for hate speech detection on social media in English, Italian, and German.

/pdf/a-multilingual-evaluation-for-online-hate-speech-detection-32t8ysihju.pdf

A Multilingual Evaluation for Online Hate Speech Detection

The application of the Universal law on migrants in documents of the United States Conference of Catholic Bishops

In this research, we showed that solitude generally has a deactivation effect on people’s affective experiences, decreasing both positive and negative high-arousal affects. In Study 1, we found that the deactivation effect occurred when people were alone, but not when they were with another person. Study 2 showed that this deactivation effect did not depend on whether or not the person was engaged in an activity such as reading when alone. In Study 3, high-arousal positive affect did not drop in a solitude condition in which participants specifically engaged in positive thinking or when they actively chose what to think about. Finally, in Study 4, we found that solitude could lead to relaxation and reduced stress when individuals actively chose to be alone. This research thus shed light on solitude effects in the past literature, and on people’s experiences when alone and the different factors that moderate these effects.

/pdf/solitude-as-an-approach-to-affective-self-regulation-k7pvqoao6b.pdf

Solitude as an Approach to Affective Self-Regulation

Spice Up Your Chat: The Intentions and Sentiment Effects of Using Emojis.

Emojis, as a new way of conveying nonverbal cues, are widely adopted in computer-mediated communications. In this paper, first from a message sender perspective, we focus on people's motives in using four types of emojis -- positive, neutral, negative, and non-facial. We compare the willingness levels of using these emoji types for seven typical intentions that people usually apply nonverbal cues for in communication. The results of extensive statistical hypothesis tests not only report the popularities of the intentions, but also uncover the subtle differences between emoji types in terms of intended uses. Second, from a perspective of message recipients, we further study the sentiment effects of emojis, as well as their duplications, on verbal messages. Different from previous studies in emoji sentiment, we study the sentiments of emojis and their contexts as a whole. The experiment results indicate that the powers of conveying sentiment are different between four emoji types, and the sentiment effects of emojis vary in the contexts of different valences.

Spice up Your Chat: The Intentions and Sentiment Effects of Using Emoji

Many aspects of people's lives are proven to be deeply connected to their jobs. In this paper, we first investigate the distinct characteristics of major occupation categories based on tweets. From multiple social media platforms, we gather several types of user information. From users' LinkedIn webpages, we learn their proficiencies. To overcome the ambiguity of self-reported information, a soft clustering approach is applied to extract occupations from crowd-sourced data. Eight job categories are extracted, including Marketing, Administrator, Start-up, Editor, Software Engineer, Public Relation, Office Clerk, and Designer. Meanwhile, users' posts on Twitter provide cues for understanding their linguistic styles, interests, and personalities. Our results suggest that people of different jobs have unique tendencies in certain language styles and interests. Our results also clearly reveal distinctive levels in terms of Big Five Traits for different jobs. Finally, a classifier is built to predict job types based on the features extracted from tweets. A high accuracy indicates a strong discrimination power of language features for job prediction task.

/pdf/what-the-language-you-tweet-says-about-your-occupation-5evto8t6nu.pdf

What the Language You Tweet Says About Your Occupation

The present research examined the role of university students’ motivation for spending time alone in their adjustment to college life, as well as the parenting correlates of students’ healthy motivation for solitude. Two studies were conducted on first-year college students in the United States (n = 147) and Canada (n = 223). In Study 1, data was collected at three different time points, separated by two-week intervals. In Study 2, data was collected at two different time points, separated by a month. The results revealed that, for those who reported perceiving lower social belonging, approaching solitary time for autonomous reasons was linked to greater self-esteem (Study 1), and greater sense of relatedness to others and lower loneliness (Study 2). These findings suggest that endorsing a healthy motivation for solitude is not necessarily indicative of social ill-being. Additionally, students’ autonomous motivation for spending time alone was associated with having parents that are autonomy supportive and that promote a sense of independence.

/pdf/embracing-me-time-motivation-for-solitude-during-transition-4rng5l9zek.pdf

Thuy-vy Nguyen

Papers

Solitude as an Approach to Affective Self-Regulation

Spice Up Your Chat: The Intentions and Sentiment Effects of Using Emojis.

Spice up Your Chat: The Intentions and Sentiment Effects of Using Emoji

What the Language You Tweet Says About Your Occupation

Embracing me-time: Motivation for solitude during transition to college