Happiness is assortative in online social networks (1103.0784v1)

Abstract: Social networks tend to disproportionally favor connections between individuals with either similar or dissimilar characteristics. This propensity, referred to as assortative mixing or homophily, is expressed as the correlation between attribute values of nearest neighbour vertices in a graph. Recent results indicate that beyond demographic features such as age, sex and race, even psychological states such as "loneliness" can be assortative in a social network. 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 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. To our knowledge this is the first result that shows assortative mixing in online networks at the level of SWB. 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 instrument in better understanding how both positive and negative sentiments spread through online social ties. Future research may focus on how event-specific mood states can propagate and influence user behavior in "real life".

An Examination of Subjective Well-Being Assortative Mixing in Twitter Social Networks

In exploring the intersection between social network characteristics and individual psychological states, Bollen et al. present a methodical investigation into how Subjective Well-Being (SWB) manifests as assortative mixing within the online milieu of Twitter. The paper captures the implications of psychological states being assortative, especially when mediated solely through digital connections, without the influence of physical interaction. This work provides pertinent insights into how virtual social environments parallel their real-world counterparts concerning the spread and clustering of emotional states.

The authors undertake a comprehensive analysis of Twitter, utilizing 129 million tweets to assess the SWB of over 102,000 users. Employing sentiment analysis tools such as OpinionFinder, the paper quantifies SWB by operationalizing the prevalence of positive versus negative terms in user tweets over a six-month period. The authors then correlate these measures of SWB with the network structures, particularly focusing on the reciprocated 'Friend' links of Twitter's otherwise directed 'Follower' network. Notably, only reciprocal follow relationships are considered indicative of genuine social ties, ensuring the robustness of the findings.

The paper notably extends existing literature by confirming the presence of assortative mixing based on SWB in an online context, which had predominantly been observed concerning demographic and some psychological traits in physical social networks. The research reveals significant pairwise and neighborhood SWB assortativity values, pinpointing a correlation of 0.443 and 0.689, respectively, for all edges, thereby affirming that Twitter users with comparable SWB values are more likely to connect.

A particularly striking aspect of this research is the exploration of the influence of edge weights on SWB assortativity. By introducing edge thresholds, the authors elucidate that assortativity intensifies amongst users with stronger, reciprocal connections. Upon considering only these stronger ties (w_ij ≥ 0.1), both the pairwise and neighborhood SWB assortativity values notably increase, stabilizing around 0.75. This finding underscores the complexity of digital social networks, where tie strength plays a crucial role in emotional congruence among users.

The research offers broader implications for understanding how online networks might be leveraged to influence digital communities' emotional atmospheres, particularly pertinent as social media continues to integrate deeply into societal fabric. The paper suggests that SWB assortativity's manifestations could facilitate mood contagion, emphasizing the potential for individuals to modify their emotional well-being by curating their online connections.

Future research suggestions include temporally dynamic analyses of user connections to discern the relative impacts of homophilic attachment versus mood contagion in driving SWB assortativity. Observing how linguistic, cultural, and geographical factors contribute could yield further nuance, as Twitter's international reach may introduce a diverse set of socio-cultural dynamics in the expression and perception of emotional content.

This paper represents a significant contribution to the understanding of emotional interplay in digital networks. It raises pertinent questions about the dual role of social media as a mirror reflecting existing psychological phenomena and as an amplifier of new network dynamics that could shape emotional and social landscapes in the future.