ANALYSIS OF THE NEWS MADE IN TURKEY ON THE COVID-19 VACCINE BY TEXT MINING METHOD
Abstract
Messages delivered to parents, providers, policy makers and the general public through the news
media can contribute to slow vaccination rates and policy action With this approach, in this study,
the headlines and contents of the news (ntotal=1981) about the COVID-19 vaccine presented in
Hürriyet and Milliyet newspapers published in Turkey (national newspapers) were examined, word
frequencies and word clouds were created. One of the main ways to quickly analyze a large dataset
is with word clouds. It was seen that the most used words in the headlines of the news were
“vaccine, Koca, virus, health and science”. In terms of content, unlike the title, it was determined
that the words “country and person” were used more than the words “Koca and science”. In
addition, the specific news about the Biontech (ntotal=254) and Sinovac (ntotal=71) vaccines
applied in Turkey were examined in the study and it was concluded that similar words were widely
used. On the other hand, it was seen that there were not many negative expressions in all the word
clouds created. Likewise, it was determined that the most emphasized phrases in the word clouds
we obtained were “Minister Fahrettin Koca” and “Science Board Member”. Based on these clues, it
was concluded that the news about the vaccine in Turkey was made for informative purposes and
that most political sources and medical doctors were cited the most.
Author(s)
Sema DÖKME YAĞAR
Çağdaş Erkan AKYÜREK
