The DOI matches its Crossref record; 74 of the 75 references it cites were found in a registry or an index.
On the Interpretation of Digital Trace Data in Communication and Social Computing Research
Abstract
The widespread availability of analytical tools for Big Data offers enormous opportunities and challenges for communication researchers. In contrast to user-generated texts, digital trace data (evidence of online user activities such as hyperlinks and retweets) represent a new methodological frontier for the field. However, interpretive strategies remain scattered and ad hoc with few best practices to guide them. To help remedy this situation, this article reviews recent scholarship in both communication and social computing research that has incorporated three common types of trace data: hyperlinks, Twitter followers, and retweets. It finds that while researchers in both fields have interpreted each trace in a variety of ways, they have largely declined to explain the validity of their interpretations.
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In the citing paper
“Norms are also sensitive to context, as the meaning of the same action or mechanism may change under different circumstances”
From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Freelon, 2014
In the citing paper
“However, this assumption has been challenged due to concerns with construct validity and stability over time (Freelon, 2014; Lazer, 2015).”
From Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries (2019) · cites this paper as Freelon, 2014
Citations
Cites
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Cited by
Sorted by citations
Baumgartner, J., Zannettou, S., Keegan, B., Squire, M., & Blackburn, J. (2020) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v14i1.7347 · Cited by 881
Social Data: Biases, Methodological Pitfalls, and Ethical Boundaries
Olteanu, A., Castillo, C., Diaz, F., & Kıcıman, E. (2019) · Frontiers in Big Data · doi:10.3389/fdata.2019.00013 · Cited by 763
“Norms are also sensitive to context, as the meaning of the same action or mechanism may change under different circumstances (Freelon, 2014).”
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Quantifying the power and consequences of social media protest
Freelon, D., McIlwain, C. D., & Clark, M. D. (2016) · New Media & Society · doi:10.1177/1461444816676646 · Cited by 392
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Metadata
- Authors
- Freelon, D.
- Affiliations
- American University (US)
- Corresponding author
- Freelon, Deen
- ORCID
- Freelon, Deen
- Venue
- Journal of Broadcasting & Electronic Media
- Publisher
- Informa UK Limited
- Published
- 2014-01-02
- Volume
- 58
- Issue
- 1
- Pages
- 59-75
- ISSN
- 0883-8151 (ISSN-L)
- 1550-6878
- OpenAlex
- W2074336863
- Cited by
- 132
- References
- 75
- Citations by year
- 2026: 15 · 2025: 5 · 2024: 13 · 2023: 10 · 2022: 8 · 2021: 15 · 2020: 14 · 2019: 12 · 2018: 14 · 2017: 6 · 2016: 8 · 2015: 9 · 2014: 2
- FWCI
- 52.16
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Broadcasting & Electronic Media (publishedVersion)
- Topics
- Social Sciences › General Social Sciences › Computational and Text Analysis Methods
- Social Sciences › Communication › Media and Digital Communication
- Social Sciences › Arts and Humanities › Literature and Literary Theory › Digital Humanities and Scholarship
- Keywords
- digital traces, interpretive strategies, hyperlinks, Twitter followers, retweets, social computing, communication research methods, big data, validity of interpretation
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