"Familiar strangers" in the big data era: An exploratory study of Beijing metro encounters. (February 2020)
- Record Type:
- Journal Article
- Title:
- "Familiar strangers" in the big data era: An exploratory study of Beijing metro encounters. (February 2020)
- Main Title:
- "Familiar strangers" in the big data era: An exploratory study of Beijing metro encounters
- Authors:
- Zhou, Jiangping
Yang, Yuling
Ma, Hanxi
Li, Ying - Abstract:
- Highlights: Redefine familiar stranger in big data era (FSiBE). Empirically operationalize FSiBE and its probable determinants. Identity determinants of FSiBE's count and odds among metro riders in Beijing. Synthesize and discuss significance of FSiBE in cities. Abstract: Traditionally, familiar strangers are defined as those we encounter and observe repeatedly in the city but never interact with. They are common to most urban dwellers. They also have various socioeconomic, sociopsychological and public-policy implications, which have only been sporadically mentioned and/or examined in existing studies across different disciplines. In this manuscript, we first summarize fragmental existing studies on familiar strangers that are defined in the traditional manner based on "small data" such as survey responses. Then we reconceptualize "familiar strangers" against the backdrop of the emergence and increased availability of big and open data. Such familiar strangers are called "familiar strangers in the big data era" (FSiBDE). After this, we have done the following: (a) synthesized and hypothesized factors influencing the distribution and quantity of the FSiBDE; (b) conducted an empirical study in the context of Beijing to embody and operationalize a special type of the FSiBDE among metro riders and to study its possible influencers. We find that across metro stations, it is spatial structure, population distribution, and transport network that significantly influence the countHighlights: Redefine familiar stranger in big data era (FSiBE). Empirically operationalize FSiBE and its probable determinants. Identity determinants of FSiBE's count and odds among metro riders in Beijing. Synthesize and discuss significance of FSiBE in cities. Abstract: Traditionally, familiar strangers are defined as those we encounter and observe repeatedly in the city but never interact with. They are common to most urban dwellers. They also have various socioeconomic, sociopsychological and public-policy implications, which have only been sporadically mentioned and/or examined in existing studies across different disciplines. In this manuscript, we first summarize fragmental existing studies on familiar strangers that are defined in the traditional manner based on "small data" such as survey responses. Then we reconceptualize "familiar strangers" against the backdrop of the emergence and increased availability of big and open data. Such familiar strangers are called "familiar strangers in the big data era" (FSiBDE). After this, we have done the following: (a) synthesized and hypothesized factors influencing the distribution and quantity of the FSiBDE; (b) conducted an empirical study in the context of Beijing to embody and operationalize a special type of the FSiBDE among metro riders and to study its possible influencers. We find that across metro stations, it is spatial structure, population distribution, and transport network that significantly influence the count and odds of FSiBDE among millions of metro riders. In addition, the FSiBDE also can have important policy and planning implications for operating metro services and managing metro station. … (more)
- Is Part Of:
- Cities. Volume 97(2020)
- Journal:
- Cities
- Issue:
- Volume 97(2020)
- Issue Display:
- Volume 97, Issue 2020 (2020)
- Year:
- 2020
- Volume:
- 97
- Issue:
- 2020
- Issue Sort Value:
- 2020-0097-2020-0000
- Page Start:
- Page End:
- Publication Date:
- 2020-02
- Subjects:
- Familiar stranger -- Big data era -- Implications -- Odds -- Distribution -- Beijing
City planning -- Periodicals
Urban policy -- Periodicals
711.4 - Journal URLs:
- http://www.sciencedirect.com/science/journal/02642751 ↗
http://www.elsevier.com/journals ↗ - DOI:
- 10.1016/j.cities.2019.102495 ↗
- Languages:
- English
- ISSNs:
- 0264-2751
- Deposit Type:
- Legaldeposit
- View Content:
- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library DSC - 3267.792160
British Library DSC - BLDSS-3PM
British Library HMNTS - ELD Digital store - Ingest File:
- 23146.xml