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Network structure and community evolution on Twitter: human behavior change in response to the 2011 Japanese earthquake and tsunami.

Lu X, Brelsford C - Sci Rep (2014)

Bottom Line: We find that while almost all users increased their online activity after the earthquake, Japanese speakers, who are assumed to be more directly affected by the event, expanded the network of people they interact with to a much higher degree than English speakers or the global average.While non-Japanese speakers did not change their conversation topics significantly after the earthquake, nearly all Japanese users changed their conversations to earthquake-related content.This study builds a systematic framework for investigating human behaviors under extreme events with online social network data and our findings on the dynamics of networks and communities may provide useful insight for understanding how patterns of social interaction are influenced by extreme events.

View Article: PubMed Central - PubMed

Affiliation: 1] College of Information System and Management, National University of Defense Technology, 410073 Changsha, China [2] Flowminder Foundation, 17177 Stockholm, Sweden [3] Department of Public Health Sciences, Karolinska Institutet, 17177 Stockholm, Sweden [4] Department of Sociology, Stockholm University, 10691 Stockholm, Sweden.

ABSTRACT
To investigate the dynamics of social networks and the formation and evolution of online communities in response to extreme events, we collected three datasets from Twitter shortly before and after the 2011 earthquake and tsunami in Japan. We find that while almost all users increased their online activity after the earthquake, Japanese speakers, who are assumed to be more directly affected by the event, expanded the network of people they interact with to a much higher degree than English speakers or the global average. By investigating the evolution of communities, we find that the behavior of joining or quitting a community is far from random: users tend to stay in their current status and are less likely to join new communities from solitary or shift to other communities from their current community. While non-Japanese speakers did not change their conversation topics significantly after the earthquake, nearly all Japanese users changed their conversations to earthquake-related content. This study builds a systematic framework for investigating human behaviors under extreme events with online social network data and our findings on the dynamics of networks and communities may provide useful insight for understanding how patterns of social interaction are influenced by extreme events.

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Illustration on the dynamics of nodes.
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f1: Illustration on the dynamics of nodes.

Mentions: Similarly to community dynamics, the dynamics of individual nodes can be modeled according to their status in a community. There are five possible behaviors for each node between time t and time t + 1. A node may stay-solitary if it does not belong to any community in time t or time t + 1; a solitary node at time t may join a community at time t + 1; a node that belongs to a community at time t may stay-social, by remaining in the same community at time t + 1, jump to another community, or leave the community and become solitary. These behaviors are shown graphically in Fig. 1.


Network structure and community evolution on Twitter: human behavior change in response to the 2011 Japanese earthquake and tsunami.

Lu X, Brelsford C - Sci Rep (2014)

Illustration on the dynamics of nodes.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4209381&req=5

f1: Illustration on the dynamics of nodes.
Mentions: Similarly to community dynamics, the dynamics of individual nodes can be modeled according to their status in a community. There are five possible behaviors for each node between time t and time t + 1. A node may stay-solitary if it does not belong to any community in time t or time t + 1; a solitary node at time t may join a community at time t + 1; a node that belongs to a community at time t may stay-social, by remaining in the same community at time t + 1, jump to another community, or leave the community and become solitary. These behaviors are shown graphically in Fig. 1.

Bottom Line: We find that while almost all users increased their online activity after the earthquake, Japanese speakers, who are assumed to be more directly affected by the event, expanded the network of people they interact with to a much higher degree than English speakers or the global average.While non-Japanese speakers did not change their conversation topics significantly after the earthquake, nearly all Japanese users changed their conversations to earthquake-related content.This study builds a systematic framework for investigating human behaviors under extreme events with online social network data and our findings on the dynamics of networks and communities may provide useful insight for understanding how patterns of social interaction are influenced by extreme events.

View Article: PubMed Central - PubMed

Affiliation: 1] College of Information System and Management, National University of Defense Technology, 410073 Changsha, China [2] Flowminder Foundation, 17177 Stockholm, Sweden [3] Department of Public Health Sciences, Karolinska Institutet, 17177 Stockholm, Sweden [4] Department of Sociology, Stockholm University, 10691 Stockholm, Sweden.

ABSTRACT
To investigate the dynamics of social networks and the formation and evolution of online communities in response to extreme events, we collected three datasets from Twitter shortly before and after the 2011 earthquake and tsunami in Japan. We find that while almost all users increased their online activity after the earthquake, Japanese speakers, who are assumed to be more directly affected by the event, expanded the network of people they interact with to a much higher degree than English speakers or the global average. By investigating the evolution of communities, we find that the behavior of joining or quitting a community is far from random: users tend to stay in their current status and are less likely to join new communities from solitary or shift to other communities from their current community. While non-Japanese speakers did not change their conversation topics significantly after the earthquake, nearly all Japanese users changed their conversations to earthquake-related content. This study builds a systematic framework for investigating human behaviors under extreme events with online social network data and our findings on the dynamics of networks and communities may provide useful insight for understanding how patterns of social interaction are influenced by extreme events.

Show MeSH