Abstract
The factors indicating influence on the social semantic web have been analysed in various approaches. We address the still open question of the temporal dynamics of these factors. We focus in particular on emerging, hot topics and the communities of microblog users around them. By training a model to predict the influence over several time segments we are able to analyse how the impact of 16 factors denoting influence develops over time. As datasets we employ a collection of microblog messages around two emerging new topics: the Egyptian revolution and the case of Dominique Strauss-Kahn being accused for sexual assault. In conclusion we demonstrate that factors indicating influence are relatively stable—even in emerging communities. In particular the characteristics of an influential user remain stable, while the characteristics of the contents they publish are less constant. However, we also observe some minor differences in our two cases that can be explained by the context of the particular topics.
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Notes
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In the preparation of this work we considered various other datasets, but had to discard them because they were either too small, did not cover a long enough time span or did not permit to extract the features we were interested in.
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Please note that performance of the fixed model is noted only from data segment 2 onwards. On the first segment it is equivalent to the local model.
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Acknowledgements
The research leading to these results has received partial funding from the European Community’s Seventh Framework Programme (FP7/2007-2013) under grant agreement no. 257859, ROBUST and grant agreement no. 287975, SocialSensor.
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Gottron, T., Radcke, O., Pickhardt, R. (2013). On the Temporal Dynamics of Influence on the Social Semantic Web. In: Li, J., Qi, G., Zhao, D., Nejdl, W., Zheng, HT. (eds) Semantic Web and Web Science. Springer Proceedings in Complexity. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-6880-6_7
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DOI: https://doi.org/10.1007/978-1-4614-6880-6_7
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