- Interrelation Between Micro-Blog Hotspots And Urban Spatial Network: An Empirical Analysis Of Tongji-Rim Intellectual-Economic-Zone, Shanghai, Based On Sina Weibo   click here to open paper content1773 kb
by    Han, Jing & Kong, Lingyu | hjbm333@163.com   click here to send an email to the auther(s) of this paper
Short Outline
This paper discusses the interrelationship between social network and urban
spatial network. It takes creative people as target group and SINA micro-
blog as platform. The basic concepts include projecting social network onto
spatial network, testing spatial traits for explanatory power of social
networks, and ranking levels of similarity.
Information technology has been making dramatic impacts on the traditional
space geography. It changed the way people understanding space, place and
time. In a Study of Manuel Castells (1989), the space of flow and the space
of place were distinguished. After revision, he argued that the space of
flow consists of the technical infrastructure network, the node and hub
network, the dominant elite network and websites. Based on this theory and
from a micro level of specific group, this paper discusses the
interrelationship between social network and urban spatial network. It
takes a large number of creative people as target group and China's most
popular social media SINA micro-blog as platform. The basic concepts
include projecting the social network onto the spatial network, testing
various spatial traits for the explanatory power of social networks, and
ranking the levels of similarity.

As creative class is the main force of a creative city, their behavioral
characteristics and spatial distribution are essential to promote the
development of the creative city and the innovation economy. Due to the
particularity of their work, creative class has closest contact with
information technology, and consequently is most influenced. Nowadays
micro-blog has become a new way of communication. Creative class gradually
form relationship networks on it. This virtual social network is set up on
the base of the physical spatial network, so there are necessary
connections between them.

The intellectual-economic-zone around Tongji University, Shanghai, is
currently China's largest design industrial cluster. It mainly homes
architectural design studios and urban planning offices and is supplemented
by various types of knowledge-based service enterprises such as education
and training, landscape design, art and media design, environmental
engineering design, automobile design, software design and engineering
consulting. There are tens of thousands of high-quality talents, making it
an ideal area to study the social network and urban spatial network of
creative class.

This paper proposes a five-step methodology. First, we collect micro-blogs
and interactive records published on the SINA micro-blogging platform by
the creative class (about 500 people) around Tongji University for a
certain period of time (a month). According to the social network analysis
approach, scale, density and centrality of the social network constructed
by the creative classare measuredandvisualized. Second, we build a three-
dimensional coordinate system using the map and the time line for
eachcreative people, mark the point of everymicro-blog (according to its
map location and time) published by the blogger in the survey duration, and
overlay allthe bloggers' data to construct a micro-blog time-
spacecube,which contains micro-blogs by all individuals.Third, according to
the results of the social network analysis, we divide the comprehensive
influence of the social network individuals into several levels, and then
replace the micro-blog points in the cubewith bubbles in different color
and size(the higher one’slevel ranks, themore striking color and larger
size his bubbleswill be drawn with). In this case, we at last achieve a
projection from the social network to the space-time cube. Fourth, based on
the map, we compute five types of graph analysis measures on spatial
networks: Reach, Gravity, Betweenness, Closenessand Straightness. Last, we
successively insertthe Reach, Gravity, Betweenness, Closeness and
Straightness map into the cube to matchthe distribution of the micro-blog
bubbles, and find out the spatial traitswhich best explain the visualized
social networks.

The results of this paper help to provide information on how to build
creative environment considering both social and spatial networks, and
develop the methodology of “Network Analysis” in space theory studies of
the information age.
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