Difference between revisions of "Fiesler, Lampe, and Bruckman (2016)"
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|Name of Study=Fiesler, Lampe, and Bruckman (2016) | |Name of Study=Fiesler, Lampe, and Bruckman (2016) | ||
− | |Author=Fiesler, C.; Lampe, C.; Bruckman, A | + | |Author=Fiesler, C.; Lampe, C.; Bruckman, A.; |
|Title=Reality and Perception of Copyright Terms of Service for Online Content Creation | |Title=Reality and Perception of Copyright Terms of Service for Online Content Creation | ||
|Year=2016 | |Year=2016 |
Latest revision as of 16:01, 9 June 2020
Contents
Source Details
Fiesler, Lampe, and Bruckman (2016) | |
Title: | Reality and Perception of Copyright Terms of Service for Online Content Creation |
Author(s): | Fiesler, C., Lampe, C., Bruckman, A. |
Year: | 2016 |
Citation: | Fiesler, C, Lampe, C, Bruckman, A (2016) “Reality and Perception of Copyright Terms of Service for Online Content Creation” CSCW ’16 Proceedings of the 19th ACM Conference on Computer-Supported Cooperative Work & Social Computing, pp1450-1461 |
Link(s): | Open Access |
Key Related Studies: | |
Discipline: | |
Linked by: | Faklaris and Hook (2017), Marshall and Shipman (2019) |
About the Data | |
Data Description: | The study uses a dataset of 30 websites (generated based on popularity for user-generated content), from which the terms of service were extracted. Other information such as word count, and reading level information was also gathered. The terms of service were analysed for readability in 2013, with a check for changes in term wording conducted in July 2014. Thereafter, a survey was issued comprising questions on 11 of the most common clauses in the terms of service. The survey was completed by 410 Mturk users. |
Data Type: | Primary data |
Secondary Data Sources: | |
Data Collection Methods: | |
Data Analysis Methods: | |
Industry(ies): | |
Country(ies): | |
Cross Country Study?: | No |
Comparative Study?: | No |
Literature review?: | No |
Government or policy study?: | No |
Time Period(s) of Collection: |
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Funder(s): |
Abstract
"From amateur creativity to social media status updates, nearly every Internet user is also a content creator—but who owns that content? Policy, including intellectual property rights, is a necessary but often invisible part of online content sharing and social computing environments. We analyzed the copyright licenses contained in the Terms of Service of 30 different websites where users contribute content, then conducted a survey to match perceptions of copyright terms to the reality. We found that licensing terms vary in unpredictable ways, and that user expectations and opinions differ by license and by type of website. Moreover, the most undesirable terms, such as right to modify, appear more frequently than users expect. We argue that users care about how their content can be used yet lack critical information. Site designers should take user needs and community norms into account in creating and explaining copyright policies."
Main Results of the Study
Users expectations of website terms of service do not align with reality. The study finds that participants could only accurately understand 69% of terms, with lower scores for less-intuitive “legalese” words such as “transferrable” or “irrevocable”. Conversely, more intuitive terms such as “display” and “worldwide” were more likely to be understood with accuracy.Users are also less likely to predict the existence of terms such as “transferrable”, “modifiable” and “irrevocable”, and furthermore generally show distaste for these types of grants. Notably, whilst users do not wish to grant these types of terms, they also do not expect them to be included within the terms of service; this suggests a misalignment with expectations and reality.
Policy Implications as Stated By Author
Rather than providing explicit policy recommendations, this study gives an analysis of users’ impressions of policy. The authors note that the role of intellectual property has become increasingly invisible, which is exacerbated by complicated language in terms of service. The study instead suggests either a design or technological intervention to introduce plain language into terms of service (perhaps by using automatic parsing). In particular, the authors suggest that by explaining what specific terms mean, and their implications, this could alleviate user concerns.
Coverage of Study
Datasets
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