1,941
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Integrating Communication Science and Computational Methods to Study Content-Based Social Media Effects

ORCID Icon, ORCID Icon, ORCID Icon, ORCID Icon & ORCID Icon

References

  • Bayer, J. B., Triệu, P., & Ellison, N. B. (2020). Social media elements, ecologies, and effects. Annual Review of Psychology, 71(1), 471–497. https://doi.org/10.1146/annurev-psych-010419-050944
  • Choukas-Bradley, S., Kilic, Z., Stout, C. D., & Roberts, S. R. (2023). Perfect storms and double-edged swords: Recent advances in research on adolescent social media use and mental health. Advances in Psychiatry and Behavioral Health, 3(1), 149–157. https://doi.org/10.1016/j.ypsc.2023.03.007
  • De Vreese, C. H., Boukes, M., Schuck, A., Vliegenthart, R., Bos, L., & Lelkes, Y. (2017). Linking survey and media content data: Opportunities, considerations, and pitfalls. Communication Methods and Measures, 11(4), 221–244. https://doi.org/10.1080/19312458.2017.1380175
  • European Commission. (2023). The Digital Services Act Package. https://digital-strategy.ec.europa.eu/en/policies/digital-services-act-package
  • Howison, J., Wiggins, A., & Crowston, K. (2011). Validity issues in the use of social network analysis with digital trace data. Journal of the Association for Information Systems, 12(12), 767–797. https://doi.org/10.17705/1jais.00282
  • The Kids Online Safety Act, S.3663, 118th Congress. (2022). https://www.blackburn.senate.gov/services/files/D89FC49B-0714-4124-B8B1-4F35A85F5E02.
  • Kleinnijenhuis, J., van Hoof, A. M. J., & van Atteveldt, W. (2019). The combined effects of mass media and social media on political perceptions and preferences. Journal of Communication, 69(6), 650–673. https://doi.org/10.1093/joc/jqz038
  • Kroon, A. C., Welbers, K., Trilling, D., & van Atteveldt, W. (2023). Using transfer-learning for measuring media effects: Challenges in automated analysis of multiple formats, languages, and modalities. Communication Methods and Measures. https://doi.org/10.1080/19312458.2023.2167197
  • Kubin, E., & von Sikorski, C. (2021). The role of (social) media in political polarization: A systematic review. Annals of the International Communication Association, 45(3), 188–206. https://doi.org/10.1080/23808985.2021.1976070
  • Lazer, D., Pentland, A., Adamic, L., Aral, S., Barabási, A. L., Brewer, D., Christakis, N., Contractor, N., Fowler, J., Gutmann, M., Jebara, T., King, G., Macy, M., Roy, D., & Van Alstyne, M. (2009). Computational Social Science: Obstacles and oppertunities. Science, 323(5915), 721–723. https://doi.org/10.1126/science.1167742
  • Ohme, J., Araujo, T., Boeschoten, L., Freelon, D., Ram, N., Reeves, B. B., & Robinson, T. N. (2023). Digital trace data collection for social media effects research: APIs, data donation, and (screen) tracking. Communication Methods and Measures, 1–18. https://doi.org/10.1080/19312458.2023.2181319
  • Otto, L. P., Loecherbach, F., & Vliegenthart, R. (2023). Linkage analysis revised – linking digital traces and survey data. Communication Methods and Measures, 1–19. https://doi.org/10.1080/19312458.2023.2257595
  • Parry, D. A., Davidson, B. I., Sewall, C. J. R., Fisher, J. T., Mieczkowski, H., & Quintana, D. S. (2021). A systematic review and meta-analysis of discrepancies between logged and self-reported digital media use. Nature Human Behaviour, 5(11), 1535–1547. https://doi.org/10.1038/s41562-021-01117-5
  • Peng, Y., Lock, I., & Sallah, A. A. (2023). Automated visual analysis for the study of social media effects: Opportunities, approaches, and challenges. Communication Methods and Measures. https://doi.org/10.1080/19312458.2023.2167197
  • Pew Research Center. (2022). Teens, social media and technology 2022. Pew Research Center. https://www.pewresearch.org/internet/2022/08/10/teens-social-media-and-technology-2022/
  • Pouwels, J. L., Valkenburg, P. M., Beyens, I., van Driel, I. I., & Keijsers, L. (2021). Some socially poor but also some socially rich adolescents feel closer to their friends after using social media. Scientific Reports, 11(1), 21176. https://doi.org/10.1038/s41598-021-99034-0. Article 21176.
  • Scharkow, M., & Bachl, M. (2017). How measurement error in content analysis and self-reported media use leads to minimal media effect findings in linkage analyses: A simulation study. Political Communication, 34(3), 323–343. https://doi.org/10.1080/10584609.2016.1235640
  • Slater, M. D. (2007). Reinforcing spirals: The mutual influence of media selectivity and media effects and their impact on individual behavior and social identity. Communication Theory, 17(3), 281–303. https://doi.org/10.1111/j.1468-2885.2007.00296.x
  • Statista. (2022). Daily Time Spent on Social Networking by Internet Users Worldwide from 2012 to 2022 (In Minutes). Statista. https://www.statista.com/statistics/433871/daily-social-media-usage-worldwide/#:~:text=How%20much%20time%20do%20peopleminutes%20in%20the%20previous%20year.
  • Valkenburg, P. M. (2017). Understanding self-effects in social media. Human Communication Research, 43(4), 477–490. https://doi.org/10.1111/hcre.12113
  • Valkenburg, P. M. (2022). Social media use and well-being: What we know and what we need to know. Current Opinion in Psychology, 45, 101294. https://doi.org/10.1016/j.copsyc.2021.12.006
  • Valkenburg, P. M., Beyens, I., Meier, A., & Vanden Abeele, M. M. P. (2022). Advancing our understanding of the associations between social media use and well-being. Current Opinion in Psychology 47, 101357. Article 101357. https://doi.org/10.1016/j.copsyc.2022.101357
  • Valkenburg, P. M., Beyens, I., Pouwels, J. L., van Driel, I. I., & Keijsers, L. (2021). Social media and adolescents’ self-esteem: Heading for a person-specific media effects paradigm. Journal of Communication, 71(1), 56–78. https://doi.org/10.1093/joc/jqaa039
  • Valkenburg, P. M., Peter, J., & Walther, J. B. (2016). Media effects: Theory and research. Annual Review of Psychology, 67(1), 315–338. https://doi.org/10.1146/annurev-psych-122414-033608
  • van Atteveldt, W., & Peng, T.-Q. (2018). When communication meets computation: Opportunities, challenges, and pitfalls in computational communication science. Communication Methods and Measures, 12(2–3), 81–92. https://doi.org/10.1080/19312458.2018.1458084
  • van Atteveldt, W., van der Velden, M. A. C. G., & Boukes, M. (2021). The validity of sentiment analysis: Comparing manual annotation, crowd-coding, dictionary approaches, and machine learning algorithms. Communication Methods and Measures, 15(2), 121–140. https://doi.org/10.1080/19312458.2020.1869198