Editorial: At the Crossroads: Lessons and Challenges in Computational Social Science
<p dir="ltr">The interest of physicists in economic and social questions is not new: during the last decades, we have witnessed the emergence of what is formally called nowadays sociophysics [1] and econophysics [2] that can be grouped into the common term “Interdisciplinary Physics”...
محفوظ في:
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| مؤلفون آخرون: | , |
| منشور في: |
2016
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إضافة وسم
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| _version_ | 1864513556414726144 |
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| author | Javier Borge-Holthoefer (211484) |
| author2 | Yamir Moreno (211486) Taha Yasseri (120975) |
| author2_role | author author |
| author_facet | Javier Borge-Holthoefer (211484) Yamir Moreno (211486) Taha Yasseri (120975) |
| author_role | author |
| dc.creator.none.fl_str_mv | Javier Borge-Holthoefer (211484) Yamir Moreno (211486) Taha Yasseri (120975) |
| dc.date.none.fl_str_mv | 2016-08-29T03:00:00Z |
| dc.identifier.none.fl_str_mv | 10.3389/fphy.2016.00037 |
| dc.relation.none.fl_str_mv | https://figshare.com/articles/journal_contribution/Editorial_At_the_Crossroads_Lessons_and_Challenges_in_Computational_Social_Science/27101647 |
| dc.rights.none.fl_str_mv | CC BY 4.0 info:eu-repo/semantics/openAccess |
| dc.subject.none.fl_str_mv | Economics Applied economics Information and computing sciences Data management and data science Human-centred computing Physical sciences computational social science simulation models big data complex systems |
| dc.title.none.fl_str_mv | Editorial: At the Crossroads: Lessons and Challenges in Computational Social Science |
| dc.type.none.fl_str_mv | Text Journal contribution info:eu-repo/semantics/publishedVersion text contribution to journal |
| description | <p dir="ltr">The interest of physicists in economic and social questions is not new: during the last decades, we have witnessed the emergence of what is formally called nowadays sociophysics [1] and econophysics [2] that can be grouped into the common term “Interdisciplinary Physics” along with biophysics, medical physics, agrophysics, etc. With tools borrowed from statistical physics and complexity science, among others, these areas of study have already made important contributions to our understanding of how humans organize and interact in our modern society. Large scale data analyses, agent-based modeling and numerical simulations, and finally mathematical modeling, have led to the discovery of new (universal) patterns and their quantitative description in socio-economic systems. At the turn of the century, however, it was clear that huge challenges—and new opportunities— lied ahead: the digital communication technologies, and their associated data deluge, began to nurture those models with empirical significance. Only a decade later, the advent of the Web 2.0, the Internet of Things and a general adoption of mobile technologies have convinced researchers that theories can be mapped to real scenarios and put into empirical test, closing in this way the experiment-theory cycle in the best tradition of physics</p><h2>Other Information</h2><p dir="ltr">Published in: Frontiers in Physics<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" rel="noreferrer noopener" target="_blank">https://creativecommons.org/licenses/by/4.0/</a> <br>See article on publisher's website: <a href="https://dx.doi.org/10.3389/fphy.2016.00037" target="_blank">https://dx.doi.org/10.3389/fphy.2016.00037</a></p> |
| eu_rights_str_mv | openAccess |
| id | Manara2_b74d5e82f480a7da5ec2162e8db7973f |
| identifier_str_mv | 10.3389/fphy.2016.00037 |
| network_acronym_str | Manara2 |
| network_name_str | Manara2 |
| oai_identifier_str | oai:figshare.com:article/27101647 |
| publishDate | 2016 |
| repository.mail.fl_str_mv | |
| repository.name.fl_str_mv | |
| repository_id_str | |
| rights_invalid_str_mv | CC BY 4.0 |
| spelling | Editorial: At the Crossroads: Lessons and Challenges in Computational Social ScienceJavier Borge-Holthoefer (211484)Yamir Moreno (211486)Taha Yasseri (120975)EconomicsApplied economicsInformation and computing sciencesData management and data scienceHuman-centred computingPhysical sciencescomputational social sciencesimulationmodelsbig datacomplex systems<p dir="ltr">The interest of physicists in economic and social questions is not new: during the last decades, we have witnessed the emergence of what is formally called nowadays sociophysics [1] and econophysics [2] that can be grouped into the common term “Interdisciplinary Physics” along with biophysics, medical physics, agrophysics, etc. With tools borrowed from statistical physics and complexity science, among others, these areas of study have already made important contributions to our understanding of how humans organize and interact in our modern society. Large scale data analyses, agent-based modeling and numerical simulations, and finally mathematical modeling, have led to the discovery of new (universal) patterns and their quantitative description in socio-economic systems. At the turn of the century, however, it was clear that huge challenges—and new opportunities— lied ahead: the digital communication technologies, and their associated data deluge, began to nurture those models with empirical significance. Only a decade later, the advent of the Web 2.0, the Internet of Things and a general adoption of mobile technologies have convinced researchers that theories can be mapped to real scenarios and put into empirical test, closing in this way the experiment-theory cycle in the best tradition of physics</p><h2>Other Information</h2><p dir="ltr">Published in: Frontiers in Physics<br>License: <a href="https://creativecommons.org/licenses/by/4.0/deed.en" rel="noreferrer noopener" target="_blank">https://creativecommons.org/licenses/by/4.0/</a> <br>See article on publisher's website: <a href="https://dx.doi.org/10.3389/fphy.2016.00037" target="_blank">https://dx.doi.org/10.3389/fphy.2016.00037</a></p>2016-08-29T03:00:00ZTextJournal contributioninfo:eu-repo/semantics/publishedVersiontextcontribution to journal10.3389/fphy.2016.00037https://figshare.com/articles/journal_contribution/Editorial_At_the_Crossroads_Lessons_and_Challenges_in_Computational_Social_Science/27101647CC BY 4.0info:eu-repo/semantics/openAccessoai:figshare.com:article/271016472016-08-29T03:00:00Z |
| spellingShingle | Editorial: At the Crossroads: Lessons and Challenges in Computational Social Science Javier Borge-Holthoefer (211484) Economics Applied economics Information and computing sciences Data management and data science Human-centred computing Physical sciences computational social science simulation models big data complex systems |
| status_str | publishedVersion |
| title | Editorial: At the Crossroads: Lessons and Challenges in Computational Social Science |
| title_full | Editorial: At the Crossroads: Lessons and Challenges in Computational Social Science |
| title_fullStr | Editorial: At the Crossroads: Lessons and Challenges in Computational Social Science |
| title_full_unstemmed | Editorial: At the Crossroads: Lessons and Challenges in Computational Social Science |
| title_short | Editorial: At the Crossroads: Lessons and Challenges in Computational Social Science |
| title_sort | Editorial: At the Crossroads: Lessons and Challenges in Computational Social Science |
| topic | Economics Applied economics Information and computing sciences Data management and data science Human-centred computing Physical sciences computational social science simulation models big data complex systems |