Abstract
Information literacy plays a crucial role in empowering social media users to effectively engage in fact-checking behaviors, thereby shielding them from becoming victims of rumors and misinformation. However, existing research predominantly treats users as a homogeneous group, neglecting potentially distinct user profiles based on their levels of information literacy. Such profiles may exhibit significant variations in users’ fact-checking behaviors, and these differences could also change over time. To bridge this research gap, the present study adopted a person-centered approach and conducted a two-wave longitudinal investigation. Using latent profile analysis, this study identified three distinct latent profiles: the information literacy proficient profile, the information literacy competent profile, and the information literacy novice profile. Additionally, based on longitudinal data analysis, this study further revealed that, in the short term, the fact-checking behavior of the information literacy competent profile exhibits no significant difference compared to that of the information literacy proficient profile, and significantly outperforms the information literacy novice profile. However, in the long term, the fact-checking behavior of the information literacy competent profile and the information literacy novice profile no longer displays significant differences. This study offers valuable insights for social media platform managers to design targeted strategies tailored to distinct user profiles.
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Acknowledgements
The work described in this paper was partially supported by the grants from the National Natural Science Foundation of China (Project No. 72274144, 72311540158), and the Humanities and Social Sciences Foundation of the Ministry of Education, China (Project No. 22YJA870013).
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Shen, XL., Wu, Y. (2024). Multidimensional Information Literacy and Fact-Checking Behavior: A Person-Centered Approach Using Latent Profile Analysis. In: Sserwanga, I., et al. Wisdom, Well-Being, Win-Win. iConference 2024. Lecture Notes in Computer Science, vol 14597. Springer, Cham. https://doi.org/10.1007/978-3-031-57860-1_20
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