Using contact tracing from interlocking diaries to map mood contagion along network chains.

Both viruses and moods are transmitted through interpersonal contacts, but it has been extremely difficult to track each unique chain of contacts through which particular moods diffuse. By analyzing 56,060 contact records from 113 interlocking, yearlong diaries collected through a web-based platform in Taiwan, we traced mood states before and after each specific contact along a triplet of persons where B contacts C and subsequently contacts A. Multilevel analyses show that both positive and negative emotions are contagious, but the two paths diverge markedly in how the diffusion stops. Positive contact between C and B (which leads to improved mood for B) spreads to A through B's contact with A, making A feel better afterward, regardless of whether B's mood deteriorated between the two interactions. Negative contact between C and B (which leads to worsened mood for B) also spreads to A, making A feel worse after the contact with B. However, the spread of a negative mood discontinues if B's mood improved between the two contacts. The different patterns of diffusion suggest that a negative mood is harder to disperse, probably because people generally make efforts to keep their negative emotions from spreading to others.

From indirect to direct contacts on Facebook: A big-data approach to the making of triadic network closure.

The rise of the Big Data paradigm has made it more feasible to track how personal networks evolve on social media, where auto-generated contact records and fine-grained temporal data sequences help capture how and when interpersonal ties and contacts change their roles. Using a sample of matched survey data and social media records, we investigated the mechanisms by which indirect contacts ("degree-2 alters") transform into direct contacts ("degree-1 alters") from a Facebook user's (ego's) point of view. To highlight the temporal sequences, we assigned different roles to the same alters depending on how each of them is connected with ego at different periods of time. Multilevel event history analyses pinpoint several online actions and network features of ego, degree-1 alters, and degree-2 alters, as the key factors that contribute to the transformation from indirect contacts into direct contacts.

L"essor du paradigme du Big Data a rendu plus réalisable le suivi de l"évolution des réseaux personnels sur les médias sociaux, où les enregistrements de contacts générés automatiquement et les séquences de données temporelles à grain fin permettent de saisir comment et quand les liens interpersonnels et les contacts changent de rôle. À l"aide d"un échantillon de données d"enquête et d"enregistrements de médias sociaux appariés, nous avons étudié les mécanismes par lesquels les contacts indirects ("altérations de degré 2″) se transforment en contacts directs ("altérations de degré 1″) du point de vue d"un utilisateur de Facebook (ego). Pour mettre en évidence les séquences temporelles, nous avons attribué des rôles différents aux mêmes alters en fonction de la façon dont chacun d"entre eux est connecté avec ego à différentes périodes de temps. Les analyses multiniveaux de l"historique des événements mettent en évidence plusieurs actions en ligne et caractéristiques du réseau d"ego, des alters de degré 1 et des alters de degré 2, comme étant les facteurs clés qui contribuent à la transformation des contacts indirects en contacts directs.

Quality of Life and Multilevel Contact Network Structures Among Healthy Adults in Taiwan: Online Participatory Cohort Study.

BACKGROUND: People's quality of life diverges on their demographics, socioeconomic status, and social connections. OBJECTIVE: By taking both demographic and socioeconomic features into account, we investigated how quality of life varied on social networks using data from both longitudinal surveys and contact diaries in a year-long (2015-2016) study. METHODS: Our 4-wave, repeated measures of quality of life followed the brief version of the World Health Organization Quality of Life scale (WHOQOL-BREF). In our regression analysis, we integrated these survey measures with key time-varying and multilevel network indices based on contact diaries. RESULTS: People's quality of life may decrease if their daily contacts contain high proportions of weak ties. In addition, people tend to perceive a better quality of life when their daily contacts are face-to-face or initiated by others or when they contact someone who is in a good mood or someone with whom they can discuss important life issues. CONCLUSIONS: Our findings imply that both functional and structural aspects of the social network play important but different roles in shaping people's quality of life.

Detecting concurrent mood in daily contact networks: an online participatory cohort study with a diary approach.

OBJECTIVES: This paper examines how people express personal mood concurrently with those connected with them by one or two degrees of separation. DESIGN: Participatory cohort study. SETTING: Online contact diary. PARTICIPANTS: 133 participants kept online diaries for 7 months in 2014, which included 127 455 contacts with 12 070 persons. MAIN OUTCOME MEASURES: Diary keepers rated a contacted person's mood during each specific contact, as well as the strength of ties between any pairs of such contacted persons. Such rich information about ties and contacts enable us to construct a complete contact network for each diary keeper, along with the network members' mood and tie strength. We calculate one's overall mood by that person's average mood score during the study period and take the shortest path between any given pair of contacted persons as the degree of separation. We further assume that two connecting persons in a contact network have made contact with each other during the study period, which allows us to examine whether and how personal moods occur concurrently within these contact networks. RESULTS: Using mixed-effects models while controlling for covariates at individual, tie and contact levels, we show that personal mood score positively and significantly correlates with the average mood among those directly tied to the person. The same effect remains positive and significant for those connected to the person by two degrees, although the effect size is reduced by about one-half. The mood of anyone separated by more than two degrees is statistically irrelevant. CONCLUSIONS: Applying network perspectives and rich data at both tie and contact levels to inquiries about subjective well-being, the current study sheds new light on how an improved diary approach can help explain the sophisticated ways in which individuals express their personal moods concurrently during social interactions in everyday life, contact by contact.

Analyzing Personal Happiness from Global Survey and Weather Data: A Geospatial Approach.

Past studies have shown that personal subjective happiness is associated with various macro- and micro-level background factors, including environmental conditions, such as weather and the economic situation, and personal health behaviors, such as smoking and exercise. We contribute to this literature of happiness studies by using a geospatial approach to examine both macro and micro links to personal happiness. Our geospatial approach incorporates two major global datasets: representative national survey data from the International Social Survey Program (ISSP) and corresponding world weather data from the National Oceanic and Atmospheric Administration (NOAA). After processing and filtering 55,081 records of ISSP 2011 survey data from 32 countries, we extracted 5,420 records from China and 25,441 records from 28 other countries. Sensitivity analyses of different intervals for average weather variables showed that macro-level conditions, including temperature, wind speed, elevation, and GDP, are positively correlated with happiness. To distinguish the effects of weather conditions on happiness in different seasons, we also adopted climate zone and seasonal variables. The micro-level analysis indicated that better health status and eating more vegetables or fruits are highly associated with happiness. Never engaging in physical activity appears to make people less happy. The findings suggest that weather conditions, economic situations, and personal health behaviors are all correlated with levels of happiness.

Contact Trees: Network Visualization beyond Nodes and Edges.

Node-Link diagrams make it possible to take a quick glance at how nodes (or actors) in a network are connected by edges (or ties). A conventional network diagram of a "contact tree" maps out a root and branches that represent the structure of nodes and edges, often without further specifying leaves or fruits that would have grown from small branches. By furnishing such a network structure with leaves and fruits, we reveal details about "contacts" in our ContactTrees upon which ties and relationships are constructed. Our elegant design employs a bottom-up approach that resembles a recent attempt to understand subjective well-being by means of a series of emotions. Such a bottom-up approach to social-network studies decomposes each tie into a series of interactions or contacts, which can help deepen our understanding of the complexity embedded in a network structure. Unlike previous network visualizations, ContactTrees highlight how relationships form and change based upon interactions among actors, as well as how relationships and networks vary by contact attributes. Based on a botanical tree metaphor, the design is easy to construct and the resulting tree-like visualization can display many properties at both tie and contact levels, thus recapturing a key ingredient missing from conventional techniques of network visualization. We demonstrate ContactTrees using data sets consisting of up to three waves of 3-month contact diaries over the 2004-2012 period, and discuss how this design can be applied to other types of datasets.

ClickDiary: Online Tracking of Health Behaviors and Mood.

BACKGROUND: Traditional studies of health behaviors are typically conducted using one-shot, cross-sectional surveys. Thus, participants' recall bias may undermine the reliability and validity of the data. To capture mood changes and health behaviors in everyday life, we designed an online survey platform, ClickDiary, which helped collect more complete information for comprehensive data analyses. OBJECTIVE: We aim to understand whether daily mood changes are related to one's personal characteristics, demographic factors, and daily health behaviors. METHODS: The ClickDiary program uses a Web-based platform to collect data on participants' health behaviors and their social-contact networks. The name ClickDiary comes from the platform's interface, which is designed to allow the users to respond to most of the survey questions simply by clicking on the options provided. Participants were recruited from the general population and came from various backgrounds. To keep the participants motivated and interested, the ClickDiary program included a random drawing for rewards. We used descriptive statistics and the multilevel proportional-odds mixed model for our analysis. RESULTS: We selected 130 participants who had completed at least 30 days of ClickDiary entries from May 1 to October 31, 2014 as our sample for the study. According to the results of the multilevel proportional-odds mixed model, a person tended to be in a better mood on a given day if he or she ate more fruits and vegetables, took in more sugary drinks, ate more fried foods, showed no cold symptoms, slept better, exercised longer, and traveled farther away from home. In addition, participants were generally in a better mood during the weekend than on weekdays. CONCLUSIONS: Sleeping well, eating more fruits and vegetables, and exercising longer each day all appear to put one in a better mood. With the online ClickDiary survey, which reduces the recall biases that are common in traditional one-shot surveys, we were able to collect and analyze the daily variations of each subject's health behaviors and mood status.

Determinants of receiving the pandemic (H1N1) 2009 vaccine and intention to receive the seasonal influenza vaccine in Taiwan.

OBJECTIVES: The paper examines the factors associated with both receiving pandemic (H1N1) 2009 vaccines and individuals' intentions to get the next seasonal influenza vaccine in Taiwan. METHODS: We conducted a representative nationwide survey with in-person household interviews during April-July 2010. Multivariate logistic regression incorporated socio-demographic background, household characteristics, health status, behaviors, and perceptions of influenza and vaccination. RESULTS: We completed interviews with 1,954 respondents. Among those, 548 (28.0%) received the pandemic (H1N1) 2009 vaccination, and 469 (24.0%) intended to get the next seasonal influenza vaccine. Receipt of the H1N1 vaccine was more prevalent among schoolchildren, the elderly, those who had contact with more people in their daily lives, and those who had received influenza vaccinations in previous years. In comparison, the intention to receive the next seasonal influenza vaccine tended to be stronger among children, the elderly, and those who reported less healthy status or lived with children, who received a seasonal influenza vaccination before, and who worried more about a possible new pandemic. CONCLUSIONS: Children, the elderly, and those who had gotten seasonal flu shots before in Taiwan were more likely to both receive a pandemic H1N1 vaccination and intend to receive a seasonal influenza vaccine.

Representative contact diaries for modeling the spread of infectious diseases in Taiwan.

Recent studies of infectious diseases have attempted to construct more realistic parameters of interpersonal contact patterns from diary-approach surveys. To ensure that such diary-based contact patterns provide accurate baseline data for policy implementation in densely populated Taiwan, we collected contact diaries from a national sample, using 3-stage systematic probability sampling and rigorous in-person interviews. A representative sample of 1,943 contact diaries recorded a total of 24,265 wide-range, face-to-face interpersonal contacts during a 24-hour period. Nearly 70% of the contacts occurred outside of respondents' households. The most active age group was schoolchildren (ages 5-14), who averaged around 16-18 daily contacts, about 2-3 times as many as the least active age groups. We show how such parameters of contact patterns help modify a sophisticated national simulation system that has been used for years to model the spread of pandemic diseases in Taiwan. Based on such actual and representative data that enable researchers to infer findings to the whole population, our analyses aim to facilitate implementing more appropriate and effective strategies for controlling an emerging or pandemic disease infection.

Internet use and academic achievement: gender differences in early adolescence.

As a new medium of learning readily connected with the outside world, the Internet has brought unprecedented opportunities to students on the one hand, while becoming a major concern for parents on the other. For parents and educators alike, it is thus critical to stipulate whether and how Internet use is linked to academic achievement. Using panel survey data from middle-school students in northern Taiwan (N = 1,409), this study examines how patterns of Internet use in the 8th grade affect students' performance on their high school entrance exam a year later. The findings confirm that online searching for information helps boost exam scores, while using the Internet for socializing and gaming, as well as going to Internet Cafés, contributes to poorer exam performance. Male and female students differ not only in their patterns of Internet use, but in how these patterns affect their academic performance. While information searching helps both boys and girls, online socializing makes girls particularly vulnerable, and online gaming and Internet Cafés hurt only boys' academic achievement.