Prospects and Challenges for the Computational Social Sciences.
(2017) In Journal of Universal Computer Science 23(11). p.1057-1069- Abstract
- Computational social sciences (CSS) refer to computer-enabled investigations of human behaviour and social interaction. They include three main components - (i) computational modelling and social simulation, (ii) the analysis of digital traces of online interactions, (iii) virtual labs and online experiments - and allow researchers to perform studies that were even hard to imagine a few decades ago. Moreover, CSS favour a more systematic test of theories and increase the possibility of study replication, two factors holding the potential to help social sciences reach a higher scientific status. Despite the huge potential of CSS, we follow previous works in identifying several impediments to a larger adoption of computational methods in... (More)
- Computational social sciences (CSS) refer to computer-enabled investigations of human behaviour and social interaction. They include three main components - (i) computational modelling and social simulation, (ii) the analysis of digital traces of online interactions, (iii) virtual labs and online experiments - and allow researchers to perform studies that were even hard to imagine a few decades ago. Moreover, CSS favour a more systematic test of theories and increase the possibility of study replication, two factors holding the potential to help social sciences reach a higher scientific status. Despite the huge potential of CSS, we follow previous works in identifying several impediments to a larger adoption of computational methods in social sciences. Most of them are linked with the humanistic attitude and a lack of technical skills of many social scientist. Significant changes in the basic training of social scientist and in the relation patterns with other disciplines and departments are needed before the potential of CSS can be fully exploited. (Less)
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/4412a304-7512-4841-b257-3d165b8b56f2
- author
- Bravo, Giangiacomo and Farjam, Mike LU
- publishing date
- 2017
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- big data, computational social sciences, experiments, social simulation, sociology
- in
- Journal of Universal Computer Science
- volume
- 23
- issue
- 11
- pages
- 13 pages
- publisher
- Technische Universitat Graz from Austria
- external identifiers
-
- scopus:85045061838
- ISSN
- 0948-695X
- language
- English
- LU publication?
- no
- id
- 4412a304-7512-4841-b257-3d165b8b56f2
- alternative location
- http://www.jucs.org/jucs_23_11/prospects_and_challenges_for
- date added to LUP
- 2021-01-20 20:58:26
- date last changed
- 2022-03-11 07:59:14
@article{4412a304-7512-4841-b257-3d165b8b56f2,
abstract = {{Computational social sciences (CSS) refer to computer-enabled investigations of human behaviour and social interaction. They include three main components - (i) computational modelling and social simulation, (ii) the analysis of digital traces of online interactions, (iii) virtual labs and online experiments - and allow researchers to perform studies that were even hard to imagine a few decades ago. Moreover, CSS favour a more systematic test of theories and increase the possibility of study replication, two factors holding the potential to help social sciences reach a higher scientific status. Despite the huge potential of CSS, we follow previous works in identifying several impediments to a larger adoption of computational methods in social sciences. Most of them are linked with the humanistic attitude and a lack of technical skills of many social scientist. Significant changes in the basic training of social scientist and in the relation patterns with other disciplines and departments are needed before the potential of CSS can be fully exploited.}},
author = {{Bravo, Giangiacomo and Farjam, Mike}},
issn = {{0948-695X}},
keywords = {{big data; computational social sciences; experiments; social simulation; sociology}},
language = {{eng}},
number = {{11}},
pages = {{1057--1069}},
publisher = {{Technische Universitat Graz from Austria}},
series = {{Journal of Universal Computer Science}},
title = {{Prospects and Challenges for the Computational Social Sciences.}},
url = {{http://www.jucs.org/jucs_23_11/prospects_and_challenges_for}},
volume = {{23}},
year = {{2017}},
}