The value of using big data technologies in computational social science
The discovery of phenomena in social networks has prompted renewed interests in the field. Data in social networks however can be massive, requiring scalable Big Data architecture. Conversely, research in Big Data needs the volume and velocity of social media data for testing its scalability. Not on...
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| Format: | Conference or Workshop Item |
| Language: | English |
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2014
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| Online Access: | https://eprints.nottingham.ac.uk/56024/ |
| _version_ | 1848799257193086976 |
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| author | Ch'ng, Eugene |
| author_facet | Ch'ng, Eugene |
| author_sort | Ch'ng, Eugene |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | The discovery of phenomena in social networks has prompted renewed interests in the field. Data in social networks however can be massive, requiring scalable Big Data architecture. Conversely, research in Big Data needs the volume and velocity of social media data for testing its scalability. Not only so, appropriate data processing and mining of acquired datasets involve complex issues in the variety, veracity, and variability of the data, after which visualisation must occur before we can see fruition in our efforts. This article presents topical, multimodal, and longitudinal social media datasets from the integration of various scalable open source technologies. The article details the process that led to the discovery of social information landscapes within the Twitter social network, highlighting the experience of dealing with social media datasets, using a funneling approach so that data becomes manageable. The article demonstrated the feasibility and value of using scalable open source technologies for acquiring massive, connected datasets for research in the social sciences. |
| first_indexed | 2025-11-14T20:32:47Z |
| format | Conference or Workshop Item |
| id | nottingham-56024 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T20:32:47Z |
| publishDate | 2014 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-560242019-02-20T11:36:52Z https://eprints.nottingham.ac.uk/56024/ The value of using big data technologies in computational social science Ch'ng, Eugene The discovery of phenomena in social networks has prompted renewed interests in the field. Data in social networks however can be massive, requiring scalable Big Data architecture. Conversely, research in Big Data needs the volume and velocity of social media data for testing its scalability. Not only so, appropriate data processing and mining of acquired datasets involve complex issues in the variety, veracity, and variability of the data, after which visualisation must occur before we can see fruition in our efforts. This article presents topical, multimodal, and longitudinal social media datasets from the integration of various scalable open source technologies. The article details the process that led to the discovery of social information landscapes within the Twitter social network, highlighting the experience of dealing with social media datasets, using a funneling approach so that data becomes manageable. The article demonstrated the feasibility and value of using scalable open source technologies for acquiring massive, connected datasets for research in the social sciences. 2014-08-07 Conference or Workshop Item PeerReviewed application/pdf en https://eprints.nottingham.ac.uk/56024/1/The%20Value%20of%20Using%20Big%20Data%20Technologies%20in%20Computational%20Social%20Science.pdf Ch'ng, Eugene (2014) The value of using big data technologies in computational social science. In: 2014 International Conference on Big Data Science and Computing, 4 -7 August 2014, Beijing, China. social network analysis; computational social science; data mining; open source;twitter http://dx.doi.org/10.1145/2640087.2644162 10.1145/2640087.2644162 10.1145/2640087.2644162 10.1145/2640087.2644162 |
| spellingShingle | social network analysis; computational social science; data mining; open source;twitter Ch'ng, Eugene The value of using big data technologies in computational social science |
| title | The value of using big data technologies in computational social science |
| title_full | The value of using big data technologies in computational social science |
| title_fullStr | The value of using big data technologies in computational social science |
| title_full_unstemmed | The value of using big data technologies in computational social science |
| title_short | The value of using big data technologies in computational social science |
| title_sort | value of using big data technologies in computational social science |
| topic | social network analysis; computational social science; data mining; open source;twitter |
| url | https://eprints.nottingham.ac.uk/56024/ https://eprints.nottingham.ac.uk/56024/ https://eprints.nottingham.ac.uk/56024/ |