Date Mining of HPV Misinformation Content in Twitter-Sphere: A Network Analytic Approach

DOI

10.2991/assehr.k.220502.054How to use a DOI?

Keywords

HPV; Social media; Misinformation content

Abstract

HPV has attracted much attention from different countries and organizations in recent years, but the vaccination rate of HPV is not high. This paper attempts to develop a “Python program” to track the “Twitter sphere content”, so as to explore the impact of social media in the process of HPV transmission and prevention. In fact, “social media” is fixed as the “channel” and tool of script, allowing users to interact and share ideas and content on digital and portal websites, which often becomes the reason for people’s “health information” all over the world. This paper mainly takes “Twitter” and other “social media” platforms to track the content of “HPV” vaccination as an example, in order to use Python language to explain the message and communication of “human papillomavirus vaccine” on “Twitter”. This paper believes that through the role of social media, we can further enrich the communication channels and produce a variety of methods to make this vaccine popular, and Twitter is one of them. At the same time, there are “four elements” of HPV vaccine error information. This research will give some enlightenment to the development and application of Python.

Copyright

© 2022 The Authors. Published by Atlantis Press SARL.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license.

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TY  - CONF
AU  - Xuantong Mou
AU  - Yilin Lan
PY  - 2022
DA  - 2022/05/14
TI  - Date Mining of HPV Misinformation Content in Twitter-Sphere: A Network Analytic Approach
BT  - Proceedings of the 2022 International Conference on Comprehensive Art and Cultural Communication (CACC 2022)
PB  - Atlantis Press
SP  - 260
EP  - 269
SN  - 2352-5398
UR  - https://doi.org/10.2991/assehr.k.220502.054
DO  - 10.2991/assehr.k.220502.054
ID  - Mou2022
ER  -