The Indonesian government began using the term “new normal” in mid-May 2020, which prompted debate in the community and was reflected on social media. Therefore, the goal of this study was to use Twitter-based social media text analysis to depict the Indonesian public’s impression of new normal conditions during the COVID-19 epidemic. We performed a text analysis on Twitter using the phrases “new normal” and “kenormalaan baru” with a time period of 1-31 July 2020 and location restrictions in Indonesia. The words associated with “new normal” are then described in a word cloud map and sorted in a flipped bar chart. We also performed a network bi-gram network analysis to identify word correlations in order to identify sentiments from Twitter text. When compared to other words, the word “covid” has the highest frequency. Other words linked with health protocols, such as “cuci” (wash), “tangan” (hand), “jaga” (maintain), and “jarak” (distance), appeared 1,138, 1501, 3.343, and 2.131 times, respectively, according to unigram analysis. Bigram network analysis reveals discrete clusters of phrases such as “protokol kesehatan” (health protocol), “wash hands” (cuci tangan), “jaga jarak” (physical distance), and “wear mask” (pakai masker). The word connections “covid,” “pandemi” (pandemic), “lupa” (forget), “maskernya” (the mask), “lakukan” (do), “social”, “distancing”, “luar” (outside), “rumah” (home) also conveyed a remark about standard measures in the new normal period.
How Social Media Text Analysis Can Inform Disaster Management
