The value of Twitter data for determining the emotional responses of people to urban green spaces: A case study and critical evaluation

被引:83
作者
Roberts, Helen [1 ]
Sadler, Jon [1 ]
Chapman, Lee [1 ]
机构
[1] Univ Birmingham, Birmingham B15 2TT, W Midlands, England
基金
英国工程与自然科学研究理事会;
关键词
built environment; method; public space; Twitter; urban green space; SOCIAL CONSTRUCTION; NEARBY NATURE; EXTINCTION; EXPERIENCE; PLACE; LANDSCAPES; HEALTH; BUFFER; SENSE;
D O I
10.1177/0042098017748544
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Interactions between humans and nature are understood to be beneficial for human well-being. In cities, urban green spaces are believed to provide many benefits to urban populations in terms of mental and emotional well-being. Through a case study of 60 urban green spaces in Birmingham, United Kingdom, this article investigates the spatial and temporal variation of the emotions experienced by individuals whilst using urban green spaces. Using a dataset obtained from Twitter as the basis for emotional explorations, sentiment analysis was performed on over 10,000 tweets to ascertain the positivity/negativity of individuals. Positive responses were more common than negative responses across all seasons, with happiness and appreciation of beauty being the common positive emotions identified. For the negative responses, fear and anger were present in similar amounts, with fewer tweets indicating sadness and disgust. Our findings show that Twitter data is a viable source of information to researchers investigating human interaction and emotional response to space in cities. Such information has implications for urban planners and park managers, enabling the creation of evidence-based spaces which enhance positive outdoor experience. Limitations in using Twitter data are discussed and these should be considered in future research.
引用
收藏
页码:818 / 835
页数:18
相关论文
共 95 条
[1]   Chatty maps: constructing sound maps of urban areas from social media data [J].
Aiello, Luca Maria ;
Schifanella, Rossano ;
Quercia, Daniele ;
Aletta, Francesco .
ROYAL SOCIETY OPEN SCIENCE, 2016, 3 (03)
[2]  
[Anonymous], INT C ADV SOC NETW A
[3]  
[Anonymous], 2012, P 8 INT C LANG RES E
[4]  
[Anonymous], 1996, The Emotional Brain
[5]  
[Anonymous], DEV GUIDE SOCIAL PRO
[6]  
[Anonymous], PARKS NAT CONS
[7]  
[Anonymous], 2013, P INT AAAI C WEB SOC
[8]  
[Anonymous], 2013, Mining the Social Web: Data Mining Facebook, Twitter, LinkedIn, Google+, GitHub, and More
[9]  
[Anonymous], MID 2014 MID POP EST
[10]  
[Anonymous], P 14 INT S W2GIS 201