scispace - formally typeset
Open AccessJournal ArticleDOI

Happiness is assortative in online social networks

Johan Bollen, +3 more
- 01 Aug 2011 - 
- Vol. 17, Iss: 3, pp 237-251
TLDR
It is shown that the general happiness, or subjective well-being, of Twitter users, as measured from a 6-month record of their individual tweets, is indeed assortative across the Twitter social network.
Abstract
Online social networking communities may exhibit highly complex and adaptive collective behaviors. Since emotions play such an important role in human decision making, how online networks modulate human collective mood states has become a matter of considerable interest. In spite of the increasing societal importance of online social networks, it is unknown whether assortative mixing of psychological states takes place in situations where social ties are mediated solely by online networking services in the absence of physical contact. Here, we show that the general happiness, or subjective well-being (SWB), of Twitter users, as measured from a 6-month record of their individual tweets, is indeed assortative across the Twitter social network. Our results imply that online social networks may be equally subject to the social mechanisms that cause assortative mixing in real social networks and that such assortative mixing takes place at the level of SWB. Given the increasing prevalence of online social networks, their propensity to connect users with similar levels of SWB may be an important factor in how positive and negative sentiments are maintained and spread through human society. Future research may focus on how event-specific mood states can propagate and influence user behavior in "real life."

read more

Content maybe subject to copyright    Report

Citations
More filters
Journal ArticleDOI

Twitter mood predicts the stock market.

TL;DR: This work investigates whether measurements of collective mood states derived from large-scale Twitter feeds are correlated to the value of the Dow Jones Industrial Average (DJIA) over time and indicates that the accuracy of DJIA predictions can be significantly improved by the inclusion of specific public mood dimensions but not others.
Journal ArticleDOI

Sentiment strength detection for the social web

TL;DR: An improved version of the algorithm SentiStrength for sentiment strength detection across the social web that primarily uses direct indications of sentiment is assessed, suggesting that, even unsupervised, Senti strength is robust enough to be applied to a wide variety of different social web contexts.
Journal ArticleDOI

Temporal Patterns of Happiness and Information in a Global Social Network: Hedonometrics and Twitter

TL;DR: Examination of expressions made on the online, global microblog and social networking service Twitter is examined, uncovering and explaining temporal variations in happiness and information levels over timescales ranging from hours to years.
Journal ArticleDOI

Cyber Hate Speech on Twitter: An Application of Machine Classification and Statistical Modeling for Policy and Decision Making

TL;DR: It is demonstrated how the results of the classifier can be robustly utilized in a statistical model used to forecast the likely spread of cyber hate in a sample of Twitter data.
Proceedings ArticleDOI

Dynamical classes of collective attention in twitter

TL;DR: A large-scale record of Twitter activity is analyzed and it is found that the evolution of hashtag popularity over time defines discrete classes of hashtags, which are linked to the events the hashtags represent and use text mining techniques to provide a semantic characterization of the hashtag classes.
References
More filters
Journal ArticleDOI

The Structure and Function of Complex Networks

Mark Newman
- 01 Jan 2003 - 
TL;DR: Developments in this field are reviewed, including such concepts as the small-world effect, degree distributions, clustering, network correlations, random graph models, models of network growth and preferential attachment, and dynamical processes taking place on networks.
Journal ArticleDOI

Birds of a Feather: Homophily in Social Networks

TL;DR: The homophily principle as mentioned in this paper states that similarity breeds connection, and that people's personal networks are homogeneous with regard to many sociodemographic, behavioral, and intrapersonal characteristics.
Posted Content

Subjective Well-Being

TL;DR: The literature on subjective well-being (SWB), including happiness, life satisfaction, and positive affect, is reviewed in three areas: measurement, causal factors, and theory.
Proceedings ArticleDOI

Flocks, herds and schools: A distributed behavioral model

TL;DR: In this article, an approach based on simulation as an alternative to scripting the paths of each bird individually is explored, with the simulated birds being the particles and the aggregate motion of the simulated flock is created by a distributed behavioral model much like that at work in a natural flock; the birds choose their own course.
Proceedings ArticleDOI

What is Twitter, a social network or a news media?

TL;DR: In this paper, the authors have crawled the entire Twittersphere and found a non-power-law follower distribution, a short effective diameter, and low reciprocity, which all mark a deviation from known characteristics of human social networks.
Related Papers (5)