By Przemyslaw Kazienko, Nitesh Chawla
This selection of contributed chapters demonstrates quite a lot of purposes inside of overlapping learn domain names: social media research and social community research. a variety of methodologies have been used in the twelve person chapters together with static, dynamic and real-time techniques to graph, textual and multimedia information research. the subjects follow to recognition computation, emotion detection, subject evolution, rumor propagation, overview of textual reviews, buddy rating, research of public transportation networks, diffusion in dynamic networks, research of individuals to groups of open resource software program builders, biometric template new release in addition to research of person habit inside heterogeneous environments of cultural academic facilities. Addressing those difficult functions is what makes this edited quantity of curiosity to researchers and scholars desirous about social media and social community analysis.
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Extra resources for Applications of Social Media and Social Network Analysis
Relationship between the new centralities and the underlying population distribution, as well as extensions to consider other modes of transportation are also among the interesting topics for future research. Acknowledgments We would like to thank the Land Transport Authority (LTA) of Singapore for sharing with us the MRT dataset. This work is supported by the National Research Foundation under its International Research Centre@Singapore Funding Initiative and administered by the IDM Programme Office, and National Research Foundation (NRF).
We apply the proposed measures on the Singapore’s subway network involving 89 stations and about 2 million commuter trips per day, and compare them with traditional topology based centrality measures. Several interesting insights about the network are derived from the new measures. We further develop a visual analytics tool to explore the different centrality measures and their changes over time. -Y. -W. -P. Lim · F. -Y. -P. sg F. sg © Springer International Publishing Switzerland 2015 P. Kazienko and N.
With this foundation research, we plan to apply the measures on other transportation networks to explore some common properties among the network centralities. We have so far assumed that the expected and alternative travel times are independent of the time of the day in our centrality definitions. This assumption will be relaxed in the future by computing the travel times at different time of the day. Relationship between the new centralities and the underlying population distribution, as well as extensions to consider other modes of transportation are also among the interesting topics for future research.