Building the Multi-Modal Storytelling of Urban Emergency Events Based on Crowdsensing of Social Media Analytics


With the development of Web 2.0, ubiquitous computing, and corresponding technologies, social media has the ability to provide the concepts of information contribution, diffusion, and exchange. Different from the permitting the general public to issue the user-generated information, social media has enabled them to avoid the need to use centralized, authoritative agencies. One of the important functions of Weibo is to monitor real time urban emergency events, such as fire, explosion, traffic jam, etc. Weibo user can be seen as social sensors and Weibo can be seen as the sensor platform. In this paper, the proposed method focuses on the step for storytelling of urban emergency events: given the Weibo posts related to a detected urban emergency event, the proposed method targets at mining the multi-modal information (e.g., images, videos, and texts), as well as storytelling the event precisely and concisely. To sum up, we propose a novel urban emergency event storytelling method to generate multi-modal summary from Weibo. Specifically, the proposed method consists of three stages: irrelevant Weibo post filtering, mining multi-modal information and storytelling generation. We conduct extensive case studies on real-world microblog datasets to demonstrate the superiority of the proposed framework.

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    A road in Shanghai, China

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    The biggest city with about 23 million people in China


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This work was supported in part by the National Science and Technology Major Project under Grant 2013ZX01033002-003, in part by the National Natural Science Foundation of China under Grant 61300202, and in part by the Science Foundation of Shanghai under Grant 13ZR1452900.

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Correspondence to Zheng Xu.

Additional information

This paper is the extended version (about 50% new content) accepted by 9th EAI International Conference on Mobile Multimedia Communications (MobiMedia 2016).

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Xu, Z., Liu, Y., Zhang, H. et al. Building the Multi-Modal Storytelling of Urban Emergency Events Based on Crowdsensing of Social Media Analytics. Mobile Netw Appl 22, 218–227 (2017).

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  • Crowdsensing
  • Emergency events
  • Multimedia storytelling
  • Social media