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Effective social relationship measurement based on user trajectory analysis

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Abstract

Social community structure is widely utilized in the study of modeling disease propagation, information dissemination and etc. Therefore, detecting the social community structure is one of the most significant tasks for majority of existing works focusing on the online social network. Traditionally, they aim at predicting the existence of social relationships based on cyber interactions (e.g. online conversation) among users. However, the strength information of social relationships is not captured which is as important as the topology information of social communities. Furthermore, physical interactions (e.g., face to face conversation), which have the potential to reflect more realistic state of social relationships than cyber ones, are not taken into account in social relationship measurement. In order to measure the strength of social relationships, in this paper, we propose a hierarchical entropy-based relationship measurement approach (HERMA). HERMA is able to measure the strength of social relationships among users based on their physical interactions which could be inferred by analyzing co-location records extracted from their trajectories. To model users’ co-location records in HERMA, a hierarchical region structure is designed. Moreover, two novel concepts called user entropy and area entropy adopted by HERMA are proposed to quantify the activeness degree of an user and the openness degree of an area respectively. Finally, to validate the effectiveness of HERMA, simulations are conducted of which the results show that HERMA outperforms the baselines by leveraging the highest average accuracy on the measurement of social relationships.

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Notes

  1. http://www.flickr.com/.

  2. http://www.facebook.com/.

  3. http://crawdad.cs.dartmouth.edu/.

  4. In the simulation, the balance splitting strategy is employed for constructing the hierarchical region structure. For example, under the setting of M=256 which means there are 256 un-overlapped unit grids in the simulation map, there is only one area consisting of 256 unit grids on the top layer. And on the layer under the top layer, there will be two un-overlapped areas while each of them is consisting of 128 unit grids. Therefore, when M = 256, it is possible to construct a hierarchical region structure with at most nine layers by employing the balance splitting strategy.

  5. For the value of T, there may be the deviation from our real life in which the duration of many valid co-location records is much longer than several seconds. In our simulation, T is set to several seconds only for the purpose of speeding up the simulation.

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Acknowledgments

This work is supported by Nokias Collaboration Grant under grant No. H-ZG19. The authors would like to thank Junjun Kong, Tao Li, Wenwen Cheng and all reviewers for their helpful suggestions and comments.

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Correspondence to Chao Ma.

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Ma, C., Cao, J., Yang, L. et al. Effective social relationship measurement based on user trajectory analysis. J Ambient Intell Human Comput 5, 39–50 (2014). https://doi.org/10.1007/s12652-012-0120-4

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