Symbiosis Evolution of Science Communication Ecosystem Based on Social Media: A Lotka–Volterra Model-Based Simulation
Social media has become an important way for science communication. Some scholars have examined how to help scientists engage with social media from operational training, policy guidance, and social media services improving. The main contribution of this study is to construct a symbiosis evolution m...
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| Format: | Article |
| Language: | English |
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Wiley
2021-01-01
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| Series: | Complexity |
| Online Access: | http://dx.doi.org/10.1155/2021/6655469 |
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| author | Ming Xia Xiangwu He Yubin Zhou |
| author_facet | Ming Xia Xiangwu He Yubin Zhou |
| author_sort | Ming Xia |
| collection | DOAJ |
| description | Social media has become an important way for science communication. Some scholars have examined how to help scientists engage with social media from operational training, policy guidance, and social media services improving. The main contribution of this study is to construct a symbiosis evolution model of science communication ecosystem (SCE) between scientists and social media platforms based on the symbiosis theory and the Lotka–Volterra model to discuss the evolution of their symbiotic patterns and population size under different symbiosis coefficients. The results indicate that (1) the size of the symbiosis coefficients determines the equilibrium outcome of the symbiosis evolution of scientists and social media platforms; (2) scientists and social media platforms can promote each other’s population size under the mutualism pattern, which can achieve sustainable science communication; (3) “1 + 1 > 2” effect can only be achieved under the symmetric mutualism pattern and the growth of scientists and social media platforms is more stable and sufficient than that of other patterns. The findings will provide additional perspectives for promoting the sustainable development of science communication based on social media. |
| format | Article |
| id | doaj-art-b607740505c34085b8a9c9252d22c263 |
| institution | Kabale University |
| issn | 1076-2787 1099-0526 |
| language | English |
| publishDate | 2021-01-01 |
| publisher | Wiley |
| record_format | Article |
| series | Complexity |
| spelling | doaj-art-b607740505c34085b8a9c9252d22c2632025-02-03T06:43:55ZengWileyComplexity1076-27871099-05262021-01-01202110.1155/2021/66554696655469Symbiosis Evolution of Science Communication Ecosystem Based on Social Media: A Lotka–Volterra Model-Based SimulationMing Xia0Xiangwu He1Yubin Zhou2School of Economics and Management, Tongji University, Shanghai 200092, ChinaBusiness School, Jiaxing University, Jiaxing 314001, ChinaSchool of Economics and Management, Tongji University, Shanghai 200092, ChinaSocial media has become an important way for science communication. Some scholars have examined how to help scientists engage with social media from operational training, policy guidance, and social media services improving. The main contribution of this study is to construct a symbiosis evolution model of science communication ecosystem (SCE) between scientists and social media platforms based on the symbiosis theory and the Lotka–Volterra model to discuss the evolution of their symbiotic patterns and population size under different symbiosis coefficients. The results indicate that (1) the size of the symbiosis coefficients determines the equilibrium outcome of the symbiosis evolution of scientists and social media platforms; (2) scientists and social media platforms can promote each other’s population size under the mutualism pattern, which can achieve sustainable science communication; (3) “1 + 1 > 2” effect can only be achieved under the symmetric mutualism pattern and the growth of scientists and social media platforms is more stable and sufficient than that of other patterns. The findings will provide additional perspectives for promoting the sustainable development of science communication based on social media.http://dx.doi.org/10.1155/2021/6655469 |
| spellingShingle | Ming Xia Xiangwu He Yubin Zhou Symbiosis Evolution of Science Communication Ecosystem Based on Social Media: A Lotka–Volterra Model-Based Simulation Complexity |
| title | Symbiosis Evolution of Science Communication Ecosystem Based on Social Media: A Lotka–Volterra Model-Based Simulation |
| title_full | Symbiosis Evolution of Science Communication Ecosystem Based on Social Media: A Lotka–Volterra Model-Based Simulation |
| title_fullStr | Symbiosis Evolution of Science Communication Ecosystem Based on Social Media: A Lotka–Volterra Model-Based Simulation |
| title_full_unstemmed | Symbiosis Evolution of Science Communication Ecosystem Based on Social Media: A Lotka–Volterra Model-Based Simulation |
| title_short | Symbiosis Evolution of Science Communication Ecosystem Based on Social Media: A Lotka–Volterra Model-Based Simulation |
| title_sort | symbiosis evolution of science communication ecosystem based on social media a lotka volterra model based simulation |
| url | http://dx.doi.org/10.1155/2021/6655469 |
| work_keys_str_mv | AT mingxia symbiosisevolutionofsciencecommunicationecosystembasedonsocialmediaalotkavolterramodelbasedsimulation AT xiangwuhe symbiosisevolutionofsciencecommunicationecosystembasedonsocialmediaalotkavolterramodelbasedsimulation AT yubinzhou symbiosisevolutionofsciencecommunicationecosystembasedonsocialmediaalotkavolterramodelbasedsimulation |