How to approach sampling for social network analysis : Facebook, Reddit, Twitter, and YouTube / Lorien Jasny, Simone Long, Jacob Minihane, Jessica Wu.
As more and more researchers use online data, thinking through how to sample this data for robust qualitative and quantitative work is critical. Many standard sampling techniques can and have been applied to large online datasets, but sampling for social network analysis can bring additional complic...
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| Online Access: |
Full Text (via SAGE) |
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| Main Authors: | , , , |
| Format: | Electronic eBook |
| Language: | English |
| Published: |
London :
SAGE Publications, Ltd.,
2022.
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| Series: | SAGE research methods: doing research online
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| Subjects: |
| Summary: | As more and more researchers use online data, thinking through how to sample this data for robust qualitative and quantitative work is critical. Many standard sampling techniques can and have been applied to large online datasets, but sampling for social network analysis can bring additional complications. Here, we think through the implications of these approaches for social network analysis using some of the most popular online social networking sites: Facebook, Reddit, Twitter, and YouTube. One of the biggest inhibitors in using data from Online Social Networks can be the limits imposed on researchers by their own application programming interface. When the rate limits are hit, researchers are often left in the dark about the sampling methods that were used to obtain the data provided. Here we discuss how researchers have handled these problems; we explore ways to sample that avoid limitations and the methods to compensate for data sampling problems should they be unavoidable. |
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| Physical Description: | 1 online resource. |
| ISBN: | 9781529610840 1529610842 |
| Source of Description, Etc. Note: | Description based on XML content. |