Volume 14 No 1 (2022): International Journal of Early Childhood Special Education
Sentiments in Leader’s Social Media Communication: Analyzing the German Chancellor on Instagram during COVID Pandemic
Keywords: Sentiment Analysis, Text Analysis, Natural Language Processing
Social media has a tremendous reach with about 3.5 billion users around the world. Therefore, also governments are already using social media platforms to reach out to their citizens. During the COVID-19 pandemic, the contact restrictions and lockdowns intensified people's need to rely on digital and social media. One method to explore this communication is referred to as “sentiment analyzes,” which attempts to automatically discover the underlying attitude about a certain entity. In this study, the social media communication of the chancellor of Germany was monitored during March 2019 and March 2021, and 610 posts towards the German citizens were collected through the analysis of APIs and Web Scraping techniques. This research will analyze the chancellor’s communication on social media before and during the covid pandemic. In order to examine how social media communication was affected in uncertain contexts and its impact on the sentiments transmitted to the German society during the COVID-19 pandemic.
IssueVolume 14 No 1 (2022): International Journal of Early Childhood Special Education
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