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Sharing social media data: The role of past experiences, attitudes, norms, and perceived behavioral control
[journal article]
Abstract Social media data (SMD) have become an important data source in the social sciences. The purpose of this paper is to investigate the experiences and practices of researchers working with SMD in their research and gain insights into researchers' sharing behavior and influencing factors for their deci... view more
Social media data (SMD) have become an important data source in the social sciences. The purpose of this paper is to investigate the experiences and practices of researchers working with SMD in their research and gain insights into researchers' sharing behavior and influencing factors for their decisions. To achieve these aims, we conducted a survey study among researchers working with SMD. The questionnaire covered different topics related to accessing, (re)using, and sharing SMD. To examine attitudes toward data sharing, perceived subjective norms, and perceived behavioral control, we used questions based on the Theory of Planned Behavior (TPB). We employed a combination of qualitative and quantitative analyses. The results of the qualitative analysis show that the main reasons for not sharing SMD were that sharing was not considered or needed, as well as legal and ethical challenges. The quantitative analyses reveal that there are differences in the relative importance of past sharing and reuse experiences, experienced challenges, attitudes, subjective norms, and perceived behavioral control as predictors of future SMD sharing intentions, depending on the way the data should be shared (publicly, with restricted access, or upon personal request). Importantly, the TPB variables have predictive power for all types of SMD sharing.... view less
Keywords
data protection; data exchange; secondary analysis; social media; data access; data capture
Classification
Methods and Techniques of Data Collection and Data Analysis, Statistical Methods, Computer Methods
Free Keywords
Big Data; Theory of Planned Behavior; data management; data reuse; data sharing; social media data
Document language
English
Publication Year
2023
Journal
Frontiers in Big Data, 5 (2023)
DOI
https://doi.org/10.3389/fdata.2022.971974
ISSN
2624-909X
Status
Published Version; peer reviewed
Licence
Creative Commons - Attribution 4.0
FundingThe publication was supported by the Leibniz Association's Open Access Publishing Fund for articles in open access journals.