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Editorial

Research Advances on User Interactions in Social Media Using Data Science Approaches

by
Felicidad García-Sánchez
1,* and
Juan Cruz-Benito
2,*
1
Fine Arts Department, University of Salamanca, 37005 Salamanca, Spain
2
IBM Quantum, IBM T.J. Watson Research Center, Yorktown Heights, NY 10598, USA
*
Authors to whom correspondence should be addressed.
Appl. Sci. 2022, 12(21), 10929; https://doi.org/10.3390/app122110929
Submission received: 24 October 2022 / Accepted: 25 October 2022 / Published: 28 October 2022
We are delighted to welcome readers to this Special Issue on “Research Advances on User Interactions in Social Media Using Data Science Approaches”. As an Internet user may perceive, new media platforms and social networks shape how individuals relate to others [1,2]. Further, there is no doubt that the contents of social networks and new media platforms define how most of society perceives itself. From news and fake news posted on social networks to images and videos [3,4,5], and their filters, to so-called challenges or new applications, such as virtual reality or augmented reality [6], the technology surrounding human communication on the internet is changing how we communicate and how we experience human interactions and human–computer interactions. Moreover, the eruption of algorithms that curate what people see and what information is received on social networks, depending on their desires, engagement, interaction, or personal information, is changing how people relate to society or their echo chambers [7]. After years of witnessing the incorporation of technological innovations in human communication and how to share our ideas with others, maybe it is time to analyze how technology affects us; how we understand what we consume on social networks and new media; and how we interact with the content and with others. Moreover, the need for an in-depth analysis is even more critical in the aftermath of the COVID-19 pandemic [8,9], a period during which millions of people worldwide interacted with others primarily via the internet. This Special Issue aims to reflect on recent research on how users interact and understand content in new media and social networks and how social networks affect users’ desires, feelings, or ideas from the perspective of Information Science and Data Science. We are sure that the papers included in this Special Issue will open up avenues for discussions on how users behave in social networks and how they experience and are exposed to information and its implications.

Author Contributions

Conceptualization and investigation: F.G.-S., J.C.-B., writing and review: F.G.-S., J.C.-B. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Acknowledgments

This paper does not represent our employer’s views.

Conflicts of Interest

The authors declare no conflict of interest.

References

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  3. García-Sánchez, F.; Therón, R.; Gómez-Isla, J. Visual Literacy in New Media: Systematic Review and Mapping of the Literature. Educ. Knowl. Soc. 2019, 20, 6-1–6-44. [Google Scholar] [CrossRef] [Green Version]
  4. García-Sánchez, F.; Gómez-Isla, J.; Therón, R.; Casado-Lumbreras, C. Assessing Visual Literacy in the Consumers of New Technologies: A Cultural Perspective. Int. J. Hum. Cap. Inf. Technol. Prof. (IJHCITP) 2019, 10, 1–21. [Google Scholar] [CrossRef] [Green Version]
  5. García-Sánchez, F.; Gómez-Isla, J.; Therón, R.; Cruz-Benito, J.; Sánchez-Prieto, J.C. Developing a Research Method to Analyze Visual Literacy Based on Cross-Cultural Characteristics. In Global Implications of Emerging Technology Trends; García-Peñalvo, F.J., Ed.; IGI Global: Hershey, PA, USA, 2018; pp. 19–33. [Google Scholar] [CrossRef] [Green Version]
  6. Flavián, C.; Ibáñez-Sánchez, S.; Orús, C. User responses towards augmented reality face filters: Implications for social media and brands. In Augmented Reality and Virtual Reality; tom Diek, M.C., Jung, T.H., Loureiro, S.M.C., Eds.; Springer: Cham, Switzerland, 2021; pp. 29–42. [Google Scholar] [CrossRef]
  7. Huszár, F.; Ktena, S.I.; O’Brien, C.; Belli, L.; Schlaikjer, A.; Hardt, M. Algorithmic amplification of politics on Twitter. Proc. Natl. Acad. Sci. USA 2021, 119, e2025334119. [Google Scholar] [CrossRef] [PubMed]
  8. Hung, M.; Lauren, E.; Hon, E.S.; Birmingham, W.C.; Xu, J.; Su, S.; Hon, S.D.; Park, J.; Dang, P.; Lipsky, M.S. Social network analysis of COVID-19 sentiments: Application of artificial intelligence. J. Med. Internet Res. 2020, 22, e22590. [Google Scholar] [CrossRef]
  9. Mourad, A.; Srour, A.; Harmanani, H.; Jenainati, C.; Arafeh, M. Critical impact of social networks infodemic on defeating coronavirus COVID-19 pandemic: Twitter-Based study and research directions. IEEE Trans. Netw. Serv. Manag. 2020, 17, 2145–2155. [Google Scholar] [CrossRef]
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MDPI and ACS Style

García-Sánchez, F.; Cruz-Benito, J. Research Advances on User Interactions in Social Media Using Data Science Approaches. Appl. Sci. 2022, 12, 10929. https://doi.org/10.3390/app122110929

AMA Style

García-Sánchez F, Cruz-Benito J. Research Advances on User Interactions in Social Media Using Data Science Approaches. Applied Sciences. 2022; 12(21):10929. https://doi.org/10.3390/app122110929

Chicago/Turabian Style

García-Sánchez, Felicidad, and Juan Cruz-Benito. 2022. "Research Advances on User Interactions in Social Media Using Data Science Approaches" Applied Sciences 12, no. 21: 10929. https://doi.org/10.3390/app122110929

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