User-centric approaches for collecting Facebook data in the ‘post-API age’: experiences from two studies and recommendations for future research

Breuer, Johannes; Kmetty, Zoltán; Haim, Mario; Stier, Sebastian

doi:10.1080/1369118x.2022.2097015

Cited by 23 publications

(17 citation statements)

References 29 publications

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“…There are accumulating examples of data donation in communications research (though few about games specifically). For example, Breuer et al (2022) asked participants to export and share parts of their Facebook data; Ohme et al (2021) asked users to donate their raw screen time data to understand measurement error associated with self-report.…”

Section: Data Donationmentioning

confidence: 99%

“…However, data donation also has unique properties for managing certain privacy and ethics concerns. Similar to other digital trace data collection methods, there are important issues at play here: for example, the fact that social media data may contain information about other people, what constitutes a fair benefit or compensation for donors, safe data storage, and more (see e.g., Breuer et al, 2022;Floridi & Krutzinna, 2019).…”

Section: Data Donationmentioning

confidence: 99%

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Four grand challenges for video game effects scholars: How digital trace data can improve the way we study games

Zendle¹,

Ballou²,

Cutting³

et al. 2023

Preprint

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The study of video game effects is currently facing four dilemmas. The first is a dilemma of causality: research should strive to contribute to our understanding of generalised causal mechanisms rather than isolated effects, but our research methodologies are often misaligned with this goal. The second is a dilemma of measurement: inappropriate use of self-report is common, and phenomena which self-report cannot measure are suppressed. The third is a dilemma of interest: personal and professional interests are frequently at odds with normative goals of scientific enquiry. Finally, we face a dilemma of speed: horizon-scanning is limited, and available methodologies are slow to address societal challenges. One solution to problems is the use of digital trace data. We describe five distinct methods for the collection of such data, ranging from the development of bespoke data infrastructure to the brokerage of data sharing agreements with industry bodies. Using our dilemmas as a lens, and drawing from our own practice as data handlers, we highlight how these methods may exacerbate or resolve each dilemma: For example, while data sharing agreements with industry unlock rapid analysis paradigms, they also present novel sites for nonfinancial conflicts of interests. Finally, we propose next steps to make digital trace data collection strategies more widespread and accessible.

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Section: Data Donationmentioning

confidence: 99%

Section: Data Donationmentioning

confidence: 99%

Four grand challenges for video game effects scholars: How digital trace data can improve the way we study games

Zendle¹,

Ballou²,

Cutting³

et al. 2023

Preprint

View full text Add to dashboard Cite

show abstract

“…Nevertheless, accessing digital social media data has recently become difficult. After the Cambridge Analytica scandal in 2018, many platforms, including Facebook decided to strongly restrict the use of Application Programming Interfaces (APIs) (Breuer et al, 2022;Bruns, 2019;Freelon, 2018), which pushed researchers to explore other, user-focused approaches, such as web-scraping (Christner et al, 2021;Mancosu & Vegetti, 2020), novel partnerships between industry and academia (King & Persily, 2020), or data donation (Boeschoten et al, 2020;Breuer et al, 2020Breuer et al, , 2022.…”

Section: Introductionmentioning

confidence: 99%

“…One key advantage of the approach is that it helps to overcome many of the privacy concerns of the API approach. Whilst in the case of platformside data collection users' ability to monitor and understand who uses their data and how they use it is limited (Halavais, 2019), user-side approaches offer users greater transparency and the chance to provide consent under clear research terms (Breuer et al, 2022). Users' data archives, moreover, provide a richer set of data compared to API or scraping approaches, which can satisfy various analytical goals or can be easily linked to other (such as survey) data.…”

Section: Introductionmentioning

confidence: 99%

“…Nevertheless, data donation is more burdensome compared to other, passive modes of data sharing (Keusch et al, 2019;Silber et al, 2022), since participants are required to actively download their data or even install a software for processing purposes, and then share it with the researchers. While data donation holds great promise to study online human behavior and some recent studies reported promising results (Baumgartner et al, 2022;Breuer et al, 2022;Kmetty & Bozsonyi, 2022;Kmetty & Németh, 2022), little is known about how to best optimize such approaches.…”

Section: Introductionmentioning

confidence: 99%

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Determinants of willingness to donate data from social media platforms

Kmetty¹,

Stefkovics²,

Szamely³

et al. 2023

Preprint

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Social media data donation through data download packages (DDPs) is a promising new way of collecting individual-level digital trace data with informed consent. When linked with survey data, data donation is an even more promising tool that helps answer novel research questions. Nevertheless, given the novelty of this approach, little is known about whether and how people would share their data with researchers, although this could seriously affect selection bias and thus, the outer validity of the results. To study the determinants of data-sharing and help future data donation studies with detecting the conditions, under which the willingness is the highest, we pre-registered two vignette experiments and embedded them in two online surveys conducted in Hungary and the U.S. In hypothetical requests for donating social media data via DDPs, we manipulated the amount of the monetary incentives (1), the presence or lack of non-monetary incentives (2), the number of requested platforms (3), the estimated upload/download time (4), and the type of requested data (5). The results revealed that data-sharing attitude is strongly subject to the parameters of the actual study, how the request is framed, and some respondent characteristics. Monetary incentives increased willingness to participate in both countries, while other effects were not consistent between the two countries. Non-monetary incentives and time to download/upload data influenced willingness in the U.S. sample but not in the Hungarian one, whereas the type of data affected the willingness to participate only in the case of the Hungarian respondents. Our findings help design more effective future data donation requests and provide insights into the potential patterns of selection bias in data donation studies.

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What's in your PIE? Understanding the contents of personalized information environments with PIEGraph

Freelon,

Pruden,

Malmer

et al. 2024

Asso for Info Science & Tech

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Social media have long been studied from platform‐centric perspectives, which entail sampling messages based on criteria such as keywords and specific accounts. In contrast, user‐centric approaches attempt to reconstruct the personalized information environments users create for themselves. Most user‐centric studies analyze what users have accessed directly through browsers (e.g., through clicks) rather than what they may have seen in their social media feeds. This study introduces a data collection system of our own design called PIEGraph that links survey data with posts collected from participants' personalized X (formerly known as Twitter) timelines. Thus, in contrast with previous research, our data include much more than what users decide to click on. We measure the total amount of data in our participants' respective feeds and conduct descriptive and inferential analyses of three other quantities of interest: political content, ideological skew, and fact quality ratings. Our results are relevant to ongoing debates about digital echo chambers, misinformation, and conspiracy theories; and our general methodological approach could be applied to social media beyond X/Twitter contingent on data availability.

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User-centric approaches for collecting Facebook data in the ‘post-API age’: experiences from two studies and recommendations for future research

Cited by 23 publications

References 29 publications

Four grand challenges for video game effects scholars: How digital trace data can improve the way we study games

Four grand challenges for video game effects scholars: How digital trace data can improve the way we study games

Determinants of willingness to donate data from social media platforms

What's in your PIE? Understanding the contents of personalized information environments with PIEGraph

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