서울형 도시 재생 활성화 대상지의 장소성 빅 데이터 분석

Abstract

Using Big Data, we analyzed and studied the experiences and perceptions of space that had been created in the past based on prior studies of locality and location image. The study chose a place called Seoul and selected four areas of government-promoted urban regeneration targets. Using Big Data, these regions were analyzed for spatial perception of their locality, and then elements that formed their location according to their regional characteristics were classified to establish their identity in today's rapidly changing urban environment and to present directions for the spatial values being reproduced in the future based on this research. Under the research method, the areas subject to the revitalization of urban regeneration were classified as areas underdeveloped with urban economic infrastructure, areas underdeveloped in the nearby areas, areas specialized in historical and cultural resources, and finally areas with the neighboring areas (general type). To examine their location and location image, we conducted a theoretical examination of the preceding study of the location components and image of the location, divided the location image into cognitive and emotional factors in Chapter 4 under the framework for analyzing big data, and finally, the keywords for analysis through a big data site called Dextom and social matrix were all selected in Korean, space, urban, orthogonal, adjectives, and verb. Research has shown that emotional factors are formed based on different cognitive factors in each region, and emotional factors play a more direct and important role in image formation than cognitive factors, and cognitive factors indirectly influence image formation through emotional factors. What appeared in common was the atmosphere at the time each region was created, which had a positive effect. A place called "recycling space" can be a place where people created a variety of memories and experiences, and a window that connects generations. Based on this research, we hope that further research will be carried out and used as directional guidelines and basic data on spatial values being reproduced in the future.