Using Big Data to study subjective well-being

被引:46
|
作者
Luhmann, Maike [1 ]
机构
[1] Ruhr Univ Bochum, Dept Psychol, Univ Str 150, D-44780 Bochum, Germany
关键词
TWITTER ANALYSIS; MEDIA LANGUAGE; TEXT ANALYSIS; FACEBOOK; HAPPINESS; SATISFACTION; VALIDITY; BEHAVIOR; TRAITS; USAGE;
D O I
10.1016/j.cobeha.2017.07.006
中图分类号
B84 [心理学]; C [社会科学总论]; Q98 [人类学];
学科分类号
03 ; 0303 ; 030303 ; 04 ; 0402 ;
摘要
Subjective well-being comprises emotional experiences and life satisfaction. This article reviews how Big Data can be used to measure, study, and change subjective well-being. Most Big Data approaches measure subjective well-being by analyzing language patterns on Twitter or Facebook. These approaches provide satisfactory accuracy for emotional experiences, but not yet for life satisfaction. Other measurement approaches include the analysis of other digital traces such as Facebook profiles and the analysis of mobile phone usage patterns. Big Data can be used to study subjective well-being on individual levels, regional levels, and across time. Potentials and limitations of using Big Data in studies on subjective well-being are discussed.
引用
收藏
页码:28 / 33
页数:6
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