A spatial econometric modeling of online social interactions using microblogs. (July 2018)
- Record Type:
- Journal Article
- Title:
- A spatial econometric modeling of online social interactions using microblogs. (July 2018)
- Main Title:
- A spatial econometric modeling of online social interactions using microblogs
- Authors:
- Wang, Zheye
Ye, Xinyue
Lee, Jay
Chang, Xiaomeng
Liu, Haimeng
Li, Qingquan - Abstract:
- Abstract: With the advent of Information and Communication technology (ICT) in modern age, the statement of "death of distance" has received numerous discussions. This article contributes a new empirical study to the debate of "death of distance" by considering the effect of spatial autocorrelation in the estimation of distance decay effect with the incorporation of network autocorrelation in spatial econometric modeling. This work is based on a city-level dataset from China's largest social networking site called Weibo. The findings are shown as following. First, the coefficient value of network autocorrelation term (0.007, significant at 0.01 level) suggests that the city-level online social links are spatially dependent. In other words, these social connections are not randomly distributed across space but tend to form spatial clusters where neighboring links are more similar. Second, controlling spatial autocorrelation in the data, a distance decay effect on the formation of online social links is unveiled with a much smaller scaling exponent of the distances (i.e., 0.276) as compared to those (e.g., 2.0, 1.8, 1.45, 1.06, 1.03, 0.4, and 0.5) in existing studies. This research provides a useful modeling framework to analyze the real-world driving forces that characterize the patterns of social interactions in virtual space and thus advance our understanding in the connection of virtual and real spaces. Highlights: A new empirical analysis of 'death of distance' thesisAbstract: With the advent of Information and Communication technology (ICT) in modern age, the statement of "death of distance" has received numerous discussions. This article contributes a new empirical study to the debate of "death of distance" by considering the effect of spatial autocorrelation in the estimation of distance decay effect with the incorporation of network autocorrelation in spatial econometric modeling. This work is based on a city-level dataset from China's largest social networking site called Weibo. The findings are shown as following. First, the coefficient value of network autocorrelation term (0.007, significant at 0.01 level) suggests that the city-level online social links are spatially dependent. In other words, these social connections are not randomly distributed across space but tend to form spatial clusters where neighboring links are more similar. Second, controlling spatial autocorrelation in the data, a distance decay effect on the formation of online social links is unveiled with a much smaller scaling exponent of the distances (i.e., 0.276) as compared to those (e.g., 2.0, 1.8, 1.45, 1.06, 1.03, 0.4, and 0.5) in existing studies. This research provides a useful modeling framework to analyze the real-world driving forces that characterize the patterns of social interactions in virtual space and thus advance our understanding in the connection of virtual and real spaces. Highlights: A new empirical analysis of 'death of distance' thesis with a Chinese microblogging dataset Spatial econometric modeling is applied to online social network. Online social connections are spatially dependent. Online social interactions are subject to geographical distance. … (more)
- Is Part Of:
- Computers, environment and urban systems. Volume 70(2018)
- Journal:
- Computers, environment and urban systems
- Issue:
- Volume 70(2018)
- Issue Display:
- Volume 70, Issue 2018 (2018)
- Year:
- 2018
- Volume:
- 70
- Issue:
- 2018
- Issue Sort Value:
- 2018-0070-2018-0000
- Page Start:
- 53
- Page End:
- 58
- Publication Date:
- 2018-07
- Subjects:
- Social media -- Death of distance -- Spatial and social network -- Spatial econometrics -- Gravity model
City planning -- Data processing -- Periodicals
Regional planning -- Data processing -- Periodicals
303.4834 - Journal URLs:
- http://www.sciencedirect.com/science/journal/01989715 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.compenvurbsys.2018.02.001 ↗
- Languages:
- English
- ISSNs:
- 0198-9715
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3394.914000
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 12881.xml