CQA services are collaborative platforms where users ask and answer questions. We investigate the influence of national culture on people's online questioning and answering behavior. For this, we analyzed a sample of 200 thousand users in Yahoo Answers from 67 countries. We measure empirically a set of cultural metrics defined in Geert Hofstede's cultural dimensions and Robert Levine's Pace of Life and show that behavioral cultural differences exist in community question answering platforms. We find that national cultures differ in Yahoo Answers along a number of dimensions such as temporal predictability of activities, contribution-related behavioral patterns, privacy concerns, and power inequality.
Quercia @cite_33 used tests and measured happiness of 32,787 Facebook users from 12 countries (Australia, Canada, France, Germany, Ireland, Italy, New Zealand, Norway, Singapore, Sweden, UK, USA ). He found that despite comparative economic status, country-level happiness significantly varies across the countries and that it strongly correlates with official well-being scores.
@cite_33
2078120282 2041003138 2110161496 1695445891
Social media sites have been used to track the expression of emotion words across nations. A question left unexplored is whether, at a similar scale, these sites can be used to collect reliable well-being data. To tackle this question, we collect Satisfaction With Life (SWL) test results from a Facebook application and show that aggregate country-level results significantly vary across twelve rich countries and strongly correlate with official well-being scores. To then show that collecting data on Facebook offers an informative look at the sociology of well-being, we study the impact of (un)happiness on the twelve countries by relating the test results on Facebook to reputable international indicators of social and health problems. We find that countries where happiness is lower have increased problems across the board: decreasing well-being is associated with increasing homicide, obesity, drug use, mental illness, and anxiety. In addition to offering these findings, this work hints at the conditions under which social media could be used for data-driven social science research. The increasing adoption of social media provides unprecedented opportunities to gain insight into human nature at vastly broader scales. Regarding the study of population-wide sentiment, prior research commonly focuses on text-based analyses and ignores a treasure trove of sentiment-laden content: images. In this paper, we make methodological and computational contributions by introducing the Smile Index as a formalized measure of societ al happiness. Detecting smiles in 9 million geo-located tweets over 16 months, we validate our Smile Index against both text-based techniques and self-reported happiness. We further make observational contributions by applying our metric to explore temporal trends in sentiment, relate public mood to societ al events, and predict economic indicators. Reflecting upon the innate, language-independent aspects of facial expressions, we recommend future improvements and applications to enable robust, global-level analyses. We conclude with implications for researchers studying and facilitating the expression of collective emotion through socio-technical systems. Objectives To evaluate whether happiness can spread from person to person and whether niches of happiness form within social networks. Design Longitudinal social network analysis. Setting Framingham Heart Study social network. Participants 4739 individuals followed from 1983 to 2003. Main outcome measures Happiness measured with validated four item scale; broad array of attributes of social networks and diverse social ties. ResultsClustersofhappyand unhappypeoplearevisible in the network, and the relationship between people ’s happiness extends up to three degrees of separation (for example, to the friends of one’s friends’ friends). People whoaresurroundedbymanyhappypeopleandthosewho arecentralinthenetworkaremorelikelytobecomehappy in the future. Longitudinal statistical models suggest that clustersofhappinessresultfromthespreadofhappiness and not just a tendency for people to associate with similarindividuals.Afriendwholiveswithinamile(about 1.6km)andwhobecomeshappyincreasestheprobability that a person is happy by 25 (95 confidence interval 1 to 57 ). Similar effects are seen in coresident spouses (8 , 0.2 to 16 ), siblings who live within a mile (14 , 1 to 28 ), and next door neighbours (34 , 7 to 70 ). Effects are not seen between coworkers. The This paper uses the Experience Sampling Method data drawn from a national sample of American youth. It examines the proximal environmental factors as well as behaviors and habits that correlate to personal happiness. Momentary-level scores show that reported happiness varies significantly both by day of week and time of day. Furthermore, particular activities are associated with varying degrees of happiness. School activities rate below average scores in happiness, while social, active and passive leisure activities are above average. Particular companions also correlate to differing level of happiness. Being alone rates the lowest levels of happiness, while being with friend corresponds to the highest. Person-level averages of happiness suggest that both higher social class and age correlate with lower levels of happiness, while gender and race do not. Paradoxically, youth who spend more time in school and social activities are happier than those who spend less. Unexpectedly, students who spend more time pleasure reading report lower levels of happiness. Finally, feeling good about the self, excited, proud, sociable, active as well as being in the conditions for flow experience are the strongest predictors of trait happiness.