Abstract—The conduct of online classes has emerged as one
of the major changes in the educational landscape at the onset of
COVID-19. Its implementation has been met by varying
reactions that have become evident in social media, particularly
on Twitter. This paper analyzed #onlineclasses tweets of
Filipino users using network analysis through Gephi and
NodeXL software. The resulting network has 2,278 users and
998 interactions with many groups of small interactions among
users, and low clustering coefficient and modularity values. The
users in the top 8 communities in the network talk about the
challenges brought about by online classes and the
opportunities that online networks offer. Hence, the network of
#OnlineClasses tweets can be described as a community cluster.
Smaller groups of users who engaged in aspects of online classes
emerge in the network, signifying that Filipinos have differing
points of view about the topic. Sentiment sharing through social
networks provides an avenue for sharing challenges and
building communities that help address challenges for online
learning in the pandemic.
Index Terms—Online classes, tweets, network analysis,
Gephi, online learning.
J. M. Sanchez and M. M. Olvido are with the Professional Education
Department, College of Teacher Education, Cebu Normal University, Cebu
City, 6000, Philippines (e-mail: sanchezj@cnu.edu.ph,
olvidom@cnu.edu.ph).
B. Alejandro is with the Integrated Laboratory School, College of
Teacher Education, Cebu Normal University, Cebu City, 6000, Philippines
(e-mail: alejandrob@cnu.edu.ph).
I. M. Alejandro is with the College of Teacher Education, and Center for
Innovative Flexible Learning, Cebu Normal University, Cebu City, 6000,
Philippines (e-mail: alejandroi@cnu.edu.ph).
Cite: Joje Mar P. Sanchez, Blanca A. Alejandro, Michelle Mae J. Olvido, and Isidro Max V. Alejandro, "An Analysis of Online Classes Tweets Using Gephi: Inputs for Online Learning," International Journal of Information and Education Technology vol. 11, no. 12, pp. 583-589, 2021.
Copyright © 2021 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).