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

References

• Araujo, T., Ausloos, J., van Atteveldt, W., Loecherbach, F., Moeller, J., Ohme, J., Trilling, D., van de Velde, B., de Vreese, C., & Welbers, K. (2021). OSD2F: An open-source data donation framework. SocArXiv, https://doi.org/10.31235/osf.io/xjk6t
   Google Scholar
• Bechmann, A., & Vahlstrup, P. B. (2015). Studying Facebook and Instagram data: The digital footprints software. First Monday, 20(12). https://doi.org/10.5210/fm.v20i12.5968
   Google Scholar
• Boeschoten, L., Ausloos, J., Moeller, J., Araujo, T., & Oberski, D. L. (2020). Digital trace data collection through data donation. arXiv preprint arXiv:2011.09851
   Google Scholar
• Brandom, R. (2021, August). Facebook shut down German research on Instagram algorithm, researchers say. The Verge. https://www.theverge.com/2021/8/13/22623354/facebook-instagram-algorithm-watch-research-legal-threat
   Google Scholar
• Breuer, J., Al Baghal, T., Sloan, L., Bishop, L., Kondyli, D., & Linardis, A. 2021). Informed consent for linking survey and social media data—Differences between platforms and data types. IASSIST Quarterly, 45(1), 1–27. https://doi.org/10.29173/iq988
   Google Scholar
• Breuer, J., Bishop, L., & Kinder-Kurlanda, K. (2020). The practical and ethical challenges in acquiring and sharing digital trace data: Negotiating public-private partnerships. New Media & Society, 22(11), 2058–2080. https://doi.org/10.1177/1461444820924622
   Web of Science ®Google Scholar
• Bruns, A. (2019). After the ‘APIcalypse’: Social media platforms and their fight against critical scholarly research. Information, Communication & Society, 22(11), 1544–1566. https://doi.org/10.1080/1369118X.2019.1637447
   Web of Science ®Google Scholar
• Christner, C., Urman, A., Adam, S., & Maier, M. (2022). Automated tracking approaches for studying online media Use: A critical review and recommendations. Communication Methods and Measures, 16(2), 79–95. https://doi.org/10.1080/19312458.2021.1907841
   Web of Science ®Google Scholar
• DeVito, M. A. (2017). From editors to algorithms. Digital Journalism, 5(6), 753–773. https://doi.org/10.1080/21670811.2016.1178592
   Web of Science ®Google Scholar
• Freelon, D. (2018). Computational research in the post-API Age. Political Communication, 35(4), 665–668. https://doi.org/10.1080/10584609.2018.1477506
   Web of Science ®Google Scholar
• Haim, M., Breuer, J., & Stier, S. (2021). Do news actually “Find Me”? Using digital behavioral data to study the news-finds-me phenomenon. Social Media + Society, 7(3). https://doi.org/10.1177/20563051211033820
   PubMed Web of Science ®Google Scholar
• Haim, M., & Nienierza, A. (2019). Computational observation. Computational Communication Research, 1(1), 79–102. https://doi.org/10.5117/CCR2019.1.004.HAIM
   Google Scholar
• Halavais, A. (2019). Overcoming terms of service: A proposal for ethical distributed research. Information, Communication & Society, 22(11), 1567–1581. https://doi.org/10.1080/1369118X.2019.1627386
   Web of Science ®Google Scholar
• Jürgens, P., Stark, B., & Magin, M. (2020). Two half-truths make a whole? On bias in self-reports and tracking data. Social Science Computer Review, 38(5), 600–615. https://doi.org/10.1177/0894439319831643
   Web of Science ®Google Scholar
• King, G. (1995). Replication, replication. PS: Political Science & Politics, 28(3), 541–559. https://doi.org/10.1017/S1049096500057607
   Web of Science ®Google Scholar
• Kmetty, Z., & Németh, R. (2022). Which is your favorite music genre? A validity comparison of Facebook data and survey data. Bulletin of Sociological Methodology/Bulletin de Méthodologie Sociologique, 154(1), 82–104. https://doi.org/10.1177/07591063211061754
   Google Scholar
• Kosinski, M., Matz, S. C., Gosling, S. D., Popov, V., & Stillwell, D. (2015). Facebook as a research tool for the social sciences: Opportunities, challenges, ethical considerations, and practical guidelines. American Psychologist, 70(6), 543–556. https://doi.org/10.1037/a0039210
   PubMed Web of Science ®Google Scholar
• Kosinski, M., Stillwell, D., & Graepel, T. (2013). Private traits and attributes are predictable from digital records of human behavior. Proceedings of the National Academy of Sciences, 110(15), 5802–5805. https://doi.org/10.1073/pnas.1218772110
   PubMed Web of Science ®Google Scholar
• Mancosu, M., & Vegetti, F. (2020). What You Can scrape and what Is right to scrape: A proposal for a tool to collect public Facebook data. Social Media + Society, 6(3). https://doi.org/10.1177/2056305120940703
   Web of Science ®Google Scholar
• Marino, C., Finos, L., Vieno, A., Lenzi, M., & Spada, M. M. (2017). Objective Facebook behaviour: Differences between problematic and non-problematic users. Computers in Human Behavior, 73, 541–546. https://doi.org/10.1016/j.chb.2017.04.015
   Web of Science ®Google Scholar
• Puschmann, C. (2019). An end to the wild west of social media research: A response to Axel Bruns. Information, Communication & Society, (11), 1582–1589. https://doi.org/10.1080/1369118x.2019.1646300
   Web of Science ®Google Scholar
• Quercia, D., Bodaghi, M., & Crowcroft, J. (2012, June 22–24). Loosing “friends” on Facebook. Proceedings of the 3rd annual ACM Web Science conference on - WebSci ‘12. https://doi.org/10.1145/2380718.2380751
   Google Scholar
• RatSWD [German Data Forum]. (2020). Big data in social, behavioural, and economic sciences: Data access and research data management. RatSWD Output, 4(6). Berlin, German Data Forum (RatSWD). https://doi.org/10.17620/02671.52
   Google Scholar
• Sandvig v. Barr. (2020). Civil Action No. 16-1368 (JDB) (United States District Court for the District of Columbia March 27, 2020). https://www.aclu.org/sandvig-v-barr-memorandum-opinion.
   Google Scholar
• Sen, I., Flöck, F., Weller, K., Weiß, B., & Wagner, C. (2021). A total error framework for digital traces of human behavior on online platforms. Public Opinion Quarterly, 85(S1), 399–422. https://doi.org/10.1093/poq/nfab018
   Google Scholar
• Skeggs, B., & Yuill, S. (2016). The methodology of a multi-model project examining how Facebook infrastructures social relations. Information, Communication & Society, 19(10), 1356–1372. https://doi.org/10.1080/1369118X.2015.1091026
   Web of Science ®Google Scholar
• Sloan, L., Jessop, C., Al Baghal, T., & Williams, M. (2020). Linking survey and Twitter data: Informed consent, disclosure, security, and archiving. Journal of Empirical Research on Human Research Ethics, 15(1–2), 63–76. https://doi.org/10.1177/1556264619853447
   PubMed Web of Science ®Google Scholar
• Statista. (2021). Number of monthly active Facebook users worldwide as of 3rd quarter 2021. https://www.statista.com/statistics/264810/number-of-monthly-active-facebook-users-worldwide/.
   Google Scholar
• Thomas, L. (2021, June). Supreme Court ruling that limits hacking law supports U-M researcher. https://news.umich.edu/supreme-court-ruling-that-limits-hacking-law-supports-u-m-researcher/
   Google Scholar
• Thorson, K., Cotter, K., Medeiros, M., & Pak, C. (2021). Algorithmic inference, political interest, and exposure to news and politics on Facebook. Information, Communication & Society, 24(2), 183–200. https://doi.org/10.1080/1369118X.2019.1642934
   Web of Science ®Google Scholar
• Vaidhya, M., Shrestha, B., Sainju, B., Khaniya, K., & Shakya, A. (2017, November 15–18). Personality traits analysis from Facebook data. The 21st International Computer Science and Engineering Conference (ICSEC), 1–5. https://doi.org/10.1109/ICSEC.2017.8443932
   Google Scholar
• Van Atteveldt, W., Althaus, S., & Wessler, H. (2021). The trouble with sharing your privates: Pursuing ethical open Science and collaborative research across national jurisdictions using sensitive data. Political Communication, 192–198. https://doi.org/10.1080/10584609.2020.1744780
   Web of Science ®Google Scholar
• Vincent, J. (2021, August). Facebook bans academics who researched ad transparency and misinformation on Facebook. The Verge. https://www.theverge.com/2021/8/4/22609020/facebook-bans-academic-researchers-ad-transparency-misinformation-nyu-ad-observatory-plug-in
   Google Scholar
• Wang, Y., Leon, P. G., Acquisti, A., Cranor, L. F., Forget, A., & Sadeh, N. (2014). A field trial of privacy nudges for Facebook. Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, 2367–2376. https://doi.org/10.1145/2556288.2557413
   Google Scholar