Uncovering Spatiotemporal Characteristics of Human Online Behaviors during Extreme Events - Supplementary Information
نویسندگان
چکیده
In response to an extreme event, individuals on social media demonstrate interesting behaviors in information seeking and sharing, depending on their backgrounds. Existing studies have attempted to analyze and understand the regularities of human responses during an extreme event, e.g., their spatiotemporal patterns. However, most of them focus on the general patterns of human collective online activities from a population perspective. In reality, individuals with different backgrounds, e.g., living in different geographic locations, will behave differently. Therefore, it remains to be a crucial issue for us to quantitatively understand human collective online behaviors during extreme events, especially from an individual perspective. Due to the difficulty in measuring individual behaviors and the lack of datasets from which the underlying dynamical processes may be inferred, it is more challenging for us to probe into the dynamics of human collective online behaviors. By making use of the large-scale datasets of posts and search queries collected from Twitter and GoogleTrends during various events, it is now possible for us to analyze individuals’ online behaviors and then reveal distinct characteristics (i.e., heterogeneous spatiotemporal patterns) of collective online responses to extreme events.
منابع مشابه
Uncovering Spatiotemporal Characteristics of Human Online Behaviors during Extreme Events
In response to an extreme event, individuals on social media demonstrate interesting behaviors depending on their backgrounds. By making use of the large-scale datasets of posts and search queries collected from Twitter and GoogleTrends, we first identify the distinct categories of human collective online concerns and durations based on the distributions of solo tweets and new incremental tweet...
متن کاملCorrection: Uncovering Spatiotemporal Characteristics of Human Online Behaviors during Extreme Events
The following information is missing from the Funding section: This work was supported by the National Natural Science Foundation of China (Nos. 61402379, 61403315), Natural Science Foundation of Chongqing (Nos. cstc2012jjA40013, cstc2013jcyjA40022) and the open project program of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education, Jilin Universty. The fun...
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