EBPVis: Visual Analytics of Economic Behavior Patterns in a Virtual Experimental Environment
Experimental economics is an important branch of economics to study human behaviours in a controlled laboratory setting or out in the field. Scientific experiments are conducted in experimental economics to collect what decisions people make in specific circumstances and verify economic theories. As...
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Published in | Computer graphics forum Vol. 43; no. 6 |
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Main Authors | , , , , , , , , , |
Format | Journal Article |
Language | English |
Published |
Oxford
Blackwell Publishing Ltd
01.09.2024
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Subjects | |
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Abstract | Experimental economics is an important branch of economics to study human behaviours in a controlled laboratory setting or out in the field. Scientific experiments are conducted in experimental economics to collect what decisions people make in specific circumstances and verify economic theories. As a significant couple of variables in the virtual experimental environment, decisions and outcomes change with the subjective factors of participants and objective circumstances, making it a difficult task to capture human behaviour patterns and establish correlations to verify economic theories. In this paper, we present a visual analytics system, EBPVis, which enables economists to visually explore human behaviour patterns and faithfully verify economic theories, e.g. the vicious cycle of poverty and poverty trap. We utilize a Doc2Vec model to transform the economic behaviours of participants into a vectorized space according to their sequential decisions, where frequent sequences can be easily perceived and extracted to represent human behaviour patterns. To explore the correlation between decisions and outcomes, an Outcome View is designed to display the outcome variables for behaviour patterns. We also provide a Comparison View to support an efficient comparison between multiple behaviour patterns by revealing their differences in terms of decision combinations and time‐varying profits. Moreover, an Individual View is designed to illustrate the outcome accumulation and behaviour patterns of subjects. Case studies, expert feedback and user studies based on a real‐world dataset have demonstrated the effectiveness and practicability of EBPVis in the representation of economic behaviour patterns and certification of economic theories.
We present a visual analytics system, EBPVis, which enables economists to visually explore human behavior patterns and faithfully verify economic theories, e.g., the vicious cycle of poverty and poverty trap. |
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AbstractList | Experimental economics is an important branch of economics to study human behaviours in a controlled laboratory setting or out in the field. Scientific experiments are conducted in experimental economics to collect what decisions people make in specific circumstances and verify economic theories. As a significant couple of variables in the virtual experimental environment, decisions and outcomes change with the subjective factors of participants and objective circumstances, making it a difficult task to capture human behaviour patterns and establish correlations to verify economic theories. In this paper, we present a visual analytics system, EBPVis, which enables economists to visually explore human behaviour patterns and faithfully verify economic theories, e.g. the vicious cycle of poverty and poverty trap. We utilize a Doc2Vec model to transform the economic behaviours of participants into a vectorized space according to their sequential decisions, where frequent sequences can be easily perceived and extracted to represent human behaviour patterns. To explore the correlation between decisions and outcomes, an Outcome View is designed to display the outcome variables for behaviour patterns. We also provide a Comparison View to support an efficient comparison between multiple behaviour patterns by revealing their differences in terms of decision combinations and time‐varying profits. Moreover, an Individual View is designed to illustrate the outcome accumulation and behaviour patterns of subjects. Case studies, expert feedback and user studies based on a real‐world dataset have demonstrated the effectiveness and practicability of EBPVis in the representation of economic behaviour patterns and certification of economic theories.
We present a visual analytics system, EBPVis, which enables economists to visually explore human behavior patterns and faithfully verify economic theories, e.g., the vicious cycle of poverty and poverty trap. Experimental economics is an important branch of economics to study human behaviours in a controlled laboratory setting or out in the field. Scientific experiments are conducted in experimental economics to collect what decisions people make in specific circumstances and verify economic theories. As a significant couple of variables in the virtual experimental environment, decisions and outcomes change with the subjective factors of participants and objective circumstances, making it a difficult task to capture human behaviour patterns and establish correlations to verify economic theories. In this paper, we present a visual analytics system, EBPVis, which enables economists to visually explore human behaviour patterns and faithfully verify economic theories, e.g. the vicious cycle of poverty and poverty trap. We utilize a Doc2Vec model to transform the economic behaviours of participants into a vectorized space according to their sequential decisions, where frequent sequences can be easily perceived and extracted to represent human behaviour patterns. To explore the correlation between decisions and outcomes, an Outcome View is designed to display the outcome variables for behaviour patterns. We also provide a Comparison View to support an efficient comparison between multiple behaviour patterns by revealing their differences in terms of decision combinations and time‐varying profits. Moreover, an Individual View is designed to illustrate the outcome accumulation and behaviour patterns of subjects. Case studies, expert feedback and user studies based on a real‐world dataset have demonstrated the effectiveness and practicability of EBPVis in the representation of economic behaviour patterns and certification of economic theories. Experimental economics is an important branch of economics to study human behaviours in a controlled laboratory setting or out in the field. Scientific experiments are conducted in experimental economics to collect what decisions people make in specific circumstances and verify economic theories. As a significant couple of variables in the virtual experimental environment, decisions and outcomes change with the subjective factors of participants and objective circumstances, making it a difficult task to capture human behaviour patterns and establish correlations to verify economic theories. In this paper, we present a visual analytics system, EBPVis , which enables economists to visually explore human behaviour patterns and faithfully verify economic theories, e.g . the vicious cycle of poverty and poverty trap. We utilize a Doc2Vec model to transform the economic behaviours of participants into a vectorized space according to their sequential decisions, where frequent sequences can be easily perceived and extracted to represent human behaviour patterns. To explore the correlation between decisions and outcomes, an Outcome View is designed to display the outcome variables for behaviour patterns. We also provide a Comparison View to support an efficient comparison between multiple behaviour patterns by revealing their differences in terms of decision combinations and time‐varying profits. Moreover, an Individual View is designed to illustrate the outcome accumulation and behaviour patterns of subjects. Case studies, expert feedback and user studies based on a real‐world dataset have demonstrated the effectiveness and practicability of EBPVis in the representation of economic behaviour patterns and certification of economic theories. |
Author | Chen, Wei Yue, Xuanwu Meng, Yuwei Wen, Jin Zhou, Zhiguang Ma, Yuming Ye, Hang Zheng, Wanjun Liu, Yuhua Shi, Qing |
Author_xml | – sequence: 1 givenname: Yuhua surname: Liu fullname: Liu, Yuhua email: liuyuhua@hdu.edu.cn organization: Hangzhou Dianzi University – sequence: 2 givenname: Yuming surname: Ma fullname: Ma, Yuming email: mamingming@hdu.edu.cn organization: Hangzhou Dianzi University – sequence: 3 givenname: Qing surname: Shi fullname: Shi, Qing email: brantqshi@hkust-gz.edu.cn organization: Hong Kong University of Science and Technology (Guangzhou) – sequence: 4 givenname: Jin surname: Wen fullname: Wen, Jin email: 231330023@hdu.edu.cn organization: Hangzhou Dianzi University – sequence: 5 givenname: Wanjun surname: Zheng fullname: Zheng, Wanjun email: zhengwanjun123@zufe.edu.cn organization: Zhejiang University of Finance & Economics – sequence: 6 givenname: Xuanwu surname: Yue fullname: Yue, Xuanwu email: xuanwu.yue@connect.ust.hk organization: Sinovation Ventures AI Institute – sequence: 7 givenname: Hang surname: Ye fullname: Ye, Hang email: hangye@zju.edu.cn organization: Zhejiang University of Finance & Economics – sequence: 8 givenname: Wei surname: Chen fullname: Chen, Wei email: chenvis@zju.edu.cn organization: Zhejiang University – sequence: 9 givenname: Yuwei surname: Meng fullname: Meng, Yuwei email: mengyuwei@zhenergy.com.cn organization: Zhejiang Provincial Energy Group Company – sequence: 10 givenname: Zhiguang orcidid: 0000-0003-2968-7830 surname: Zhou fullname: Zhou, Zhiguang email: zhgzhou@hdu.edu.cn organization: Zhejiang University |
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