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Mining web-based data to assess public response to environmental events

机译:挖掘基于网络的数据以评估公众对环境事件的反应

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摘要

We explore how the analysis of web-based data, such as Twitter and Google Trends, can be used to assess the social relevance of an environmental accident. The concept and methods are applied in the shutdown of drinking water supply at the city of Toledo, Ohio, USA. Toledo's notice, which persisted from August 1 to 4, 2014, is a high-profile event that directly influenced approximately half a million people and received wide recognition. The notice was given when excessive levels of microcystin, a byproduct of cyanobacteria blooms, were discovered at the drinking water treatment plant on Lake Erie. Twitter mining results illustrated an instant response to the Toledo incident, the associated collective knowledge, and public perception. The results from Google Trends, on the other hand, revealed how the Toledo event raised public attention on the associated environmental issue, harmful algal blooms, in a long-term context. Thus, when jointly applied, Twitter and Google Trend analysis results offer complementary perspectives. Web content aggregated through mining approaches provides a social standpoint, such as public perception and interest, and offers context for establishing and evaluating environmental management policies.
机译:我们探索如何对基于Web的数据(例如Twitter和Google趋势)进行分析,以评估环境事故的社会相关性。该概念和方法已应用于美国俄亥俄州托莱多市的饮用水供应关闭中。托莱多的通知一直持续到2014年8月1日至4日,是一次备受瞩目的活动,直接影响了大约50万人,并获得了广泛认可。当在伊利湖上的饮用水处理厂发现过量水平的微囊藻毒素时,发出通知。 Twitter的挖掘结果说明了对托莱多事件,相关的集体知识和公众看法的即时响应。另一方面,Google趋势的结果显示,从长远来看,托莱多事件如何引起公众对相关环境问题(有害藻华)的关注。因此,在联合应用时,Twitter和Google趋势分析结果提供了互补的观点。通过挖掘方法聚合的Web内容提供了一种社会立场,例如公众的感知和兴趣,并为建立和评估环境管理政策提供了环境。

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