Identifikasi Pandemic Fatigue COVID-19 pada Bulan Februari-Desember 2021 melalui Media Sosial Twitter

DINA ARIFKA, Haryanto, Drs., M.Si., Psikolog

2022 | Skripsi | S1 PSIKOLOGI

Kasus pandemi COVID-19 yang terus meningkat di awal tahun 2021, tidak diiringi dengan peningkatan penerapan protokol kesehatan oleh masyarakat. Penelitian ini mengkaji mengenai sentimen masyarakat di media sosial Twitter dan berusaha mengungkap faktor apa saja yang memunculkan adanya indikasi pandemic fatigue. Metode penelitian menggunakan etnometodologi dengan pendekatan etnografi digital. Analisis data menggunakan analisis sentimen dengan algoritma Valence Aware Dictionary for Sentiment Reasoner (VADER) dan analisis topic modeling dengan algoritma Latent Dirichlet Allocation (LDA) yang diolah menggunakan software Orange Data Mining versi 3.30. Hasil penelitian menunjukkan bahwa pada Februari-Desember 2021 sentiment masyarakat terkait protokol kesehatan didominasi oleh sentimen netral, sedangkan berdasarkan perhitungan skor compound ditemukan adanya tiga kali penurunan grafik sentiment yang mengindikasikan adanya fenomena pandemic fatigue. Penurunan grafik sentimen ini dipengaruhi oleh beberapa faktor di antaranya pengalaman vaksinasi, berita vaksinasi, ketakutan untuk vakisn, dan kritik masyarakat dalam upaya mengontrol penyebaran COVID-19.

COVID-19 pandemic cases that continuously increased in the early 2021 are not followed by publics awareness on health protocols. This study examines public sentiment on Twitter, a social media platform, and knows what factors that affects the rising indications of pandemic fatigue. The method of this research uses ethnomethodology with a digital ethnographic approach. Data analysis were performed by sentiment analysis with Valence Aware Dictionary for Sentiment Reasoner (VADER) algorithm and topic modeling analysis with Latent Dirichlet Allocation (LDA) algorithm that processed by software from Orange Data Mining version 3.30. The results showed that during February-December 2021 public sentiment regarding health protocols is dominated by neutral sentiment, while based on the calculation of the compound score, there were three times degrassion in the sentiment graph indicating the phenomenon of pandemic fatigue. The degression in the sentiment graph was influenced by several factors including vaccination experience, vaccination news, fear of vaccines, and public criticism of efforts to control the spread of COVID-19.

Kata Kunci : COVID-19, Pandemic Fatigue, Analisis Sentimen, Pemodelan Topik