Developing a Framework for an Advisory Message Board for Female Victims after Disasters: A Case Study after East Japan Great Earthquake
Developing a Framework for an Advisory Message Board for Female Victims after Disasters: A Case Study after East Japan Great Earthquake
复制标题
为灾后女性受害者咨询留言板制定框架：东日本大地震后的案例研究
DOI：
10.1093/llc/fqv017
复制
发表时间：
2015
影响因子：
0.8
通讯作者：
Basabi Chakraborty
中科院分区：
文献类型：
--
作者：
Takako Hashimoto;Yukari Shirota;Basabi Chakraborty
2011年3月11日东日本大地震突然发生后，三重灾害使东日本市民的正常生活陷入瘫痪。很多人都受到了影响，尤其是女性受害者，她们面临着不同的问题和担忧：她们必须照顾老人、抚养孩子、找新工作。妇女对日常生活用品也有特殊的需求。行政当局希望认识到妇女受害者的具体问题，并向她们提供适当的支助。然而，很难正确把握女性受害者的需求，因为她们确实很有耐心，她们的需求有时在环境压力下被忽视。对女性受害者进行访谈和问卷调查是衡量她们需求的一种方法，但这既耗时又费力。这项工作提出了一个框架，为网络上的妇女受害者建立一个咨询留言板，妇女受害者可以在该留言板上自由发表信息。计算技术在这里用于分析数字媒体数据，以便在地震等灾害中改善服务不足或贫困人口的生活。开发了文字挖掘技术，自动分析讯息，找出受害者的具体需要和需要随时间的变化，并向他们提供适当的建议。该方法使用潜在语义分析（LSA）来提取隐藏主题和主题随时间的变化。作为一个案例研究，我们收集并分析了东日本大地震后两年多时间里几个在线社交媒体上的短信。研究发现，与基于图的主题提取方法相比，基于lsa的技术在提取需求随时间的变化方面更有效。这项工作的最终目的是建立妇女咨询留言板框架，帮助当局在今后发生任何灾害后发现妇女受害者的特殊需要并向她们提供支助。
After the sudden occurrence of East Japan Great Earthquake on 11 March 2011, triple disasters crippled the regular life of citizens of East Japan. A lot of people were affected, especially women victims suffered from different problems and worries: they had to care for elders, raise children, and find new jobs. Women also had specific needs of commodities for everyday life. Administrative authorities wanted to recognize women victims’ specific problems and provide them appropriate supports. However, it was difficult to grasp women victims’ requirements properly, because they were really patient and their needs were sometimes neglected under the environmental pressure. Conducting interviews and taking questionnaire from women victims is one way to gauge their needs, but it is time-consuming and labor intensive. This work proposes a framework for the development of an advisory message board for women victims on the web in which women victims can post their messages freely. The computational technologies are used here for analyzing digital media data in order to improve the lives of underserved or underprivileged people in case of disasters like earthquake. Text mining technologies are developed for automatic analysis of the messages to find out the specific needs of the victims and the change of needs with time and support them with proper advice. The proposed method uses latent semantic analysis (LSA) to extract the hidden topics and change of topics over time. As a case study, text messages from several on-line social media over a period of 2 years after the East Japan Great earthquake are collected and analyzed. It has been found that LSA-based technique is more effective in extracting the change of needs over time than graph-based topic extraction method. The final aim of this work is to develop the framework of advisory message board for women which will help the authority to find out the special needs of women victims after any future disaster and support them.