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Text Mining in Smart Cities to Identify Urban Events and Public Service Problems

机译:智能城市的文本挖掘,以确定城市活动和公共服务问题

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Cities will be constituted in large agglomerations and will be the axis of social, economic, cultural, and artistic human activity. According to the latest United Nations reports, in 2050, the cities will concentrate on 68% of the world's population; this means that progressively the world will no longer be rural and will become urban. Local governments can benefit of the ICTs in order to collect data and make smarter decision and policy making for such large cities. The Smart Cities will be related to the use of social networks and social mining to be able to analyze the opinions of citizens and their reactions to the governors or governmental entities. Currently, social networks such as Twitter have provided the opportunity to perform analysis on the user interactions and sentiments. We intend to apply a tweets text mining process to identify public service problems and urban events related, for instance, traffic and security. A case study in Ecuador capital Quito and its metropolitan area. The present research allows identifying, on the one hand, the inconveniences/problems related to public services and urban events such as water, electricity, mobility, public transport, and security at the level of different areas. A temporal and spatial identification of such problems is also carried out.
机译:城市将在巨大的附注中构成,将是社会,经济,文化和艺术人类活动的轴。根据最新的联合国报告,在2050年,城市将集中在世界上68%的人口;这意味着世界逐步将不再是农村,并将成为城市。地方政府可以利用信息通信技术,以便收集数据并为这类大城市进行更聪明的决定和政策制定。智能城市将与社会网络和社交挖掘的使用有关,以便能够分析公民的意见及其对州长或政府实体的反应。目前,Twitter等社交网络已经提供了对用户交互和情绪进行分析的机会。我们打算申请推文文本挖掘过程,以确定例如交通和安全相关的公共服务问题和城市事件。厄瓜多尔首都基多及其大都市区案例研究。本研究允许一方面识别与公共服务和城市活动相关的不便/问题,例如水,电力,流动性,公共交通和在不同地区的水平处的安全性。还进行了这些问题的时间和空间识别。

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