Claim Missing Document
Check
Articles

Found 2 Documents
Search

Impact of Social Media Use on Public Behavior Regarding COVID-19 Vaccination Refusal Juliadi, Rismi; Angelia, Chininta Rizka; Faramita, Aazelia
JURNAL KOMUNIKASI INDONESIA Vol. 14, No. 1
Publisher : UI Scholars Hub

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

This study explores the impact of social media use on the behavior related to the refusal of the COVID-19 vaccination. Social media has been one of the most widely used sources of information during the COVID-19 pandemic. It provides easy access to a wide range of content, including information about the COVID-19 vaccination campaign carried out by the Indonesian government. However, content shared via social media is vulnerable to disinformation, fake news, and hoaxes. The use of social media during the pandemic has had a significant impact on people's attitudes toward vaccination, with vaccine hesitancy often stemming from multiple factors. This study aims to measure the impact of social media usage on behavior related to COVID-19 vaccination refusal. The research is grounded in the Uses and Gratification Theory (UGT) and the Theory of Planned Behavior (TPB), and employs a quantitative-explanatory research method. Data were collected via a survey of 196 respondents from generation X and Y, selected using a purposive sampling technique. The data analysis was conducted using Structural Equation Modelling (SEM) - Partial Least Square (PLS). Among the respondents—62% females and 38% males—the majority reported receiving an invitation from the Ministry of Health to participate in the vaccination program. The findings reveal a significant and nuanced distinction among the variables of information seeking and status seeking. Notably, purpose-driven or interactive social media activities were not significant predictors of vaccine refusal. In contrast, social media use for entertainment purposes emerged as a strong and statistically significant predictor of vaccine refusal behavior. This key finding suggests that passive consumption of entertainment-oriented content—such as memes, viral videos, or influencer narratives—may influence vaccine attitudes more powerfully than overtly persuasive or informative content. It appears that such content can bypass the critical scrutiny applied during active information-seeking behavior, thereby making entertainment-based media a potent vector for misinformation and vaccine hesitancy. The implication of this study reveals that the “entertainment” motive is the only significant predictor of the refusal of the COVID-19 vaccination, indicating that purely informational or data-heavy campaigns are ineffective against entertainment-driven misinformation. Therefore, public health communication should evolve toward emotionally engaging, narrative-based, and entertainment-oriented strategies, leveraging influencers, storytelling, and positive framing to foster hope, responsibility, and pro-vaccine behavior.
Understanding User Satisfaction in Digital Finance Through Sentiment Analysis of User Reviews Angelia, Chininta Rizka; Nurhayati, Kristina; Amalia, Dinda
Journal of Digital Market and Digital Currency Vol. 2 No. 4 (2025): Regular Issue December 2025
Publisher : Bright Publisher

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.47738/jdmdc.v2i4.45

Abstract

This study conducted a sentiment analysis on 100,000 user reviews of the Kredivo app to assess user satisfaction and identify areas for improvement in the context of digital finance. Leveraging Term Frequency-Inverse Document Frequency (TF-IDF) for feature extraction and employing Logistic Regression and Support Vector Machine (SVM) models, the analysis revealed a predominantly positive user sentiment, with 62% of the reviews classified as positive, 25% as negative, and 13% as neutral. Positive reviews frequently highlighted the app's ease of use and quick access to credit, indicating high satisfaction with its functionality and convenience. In contrast, negative reviews commonly cited issues with customer service responsiveness and transparency around fees, suggesting areas where the app could enhance user experience. Visualizations, including a confusion matrix and sentiment distribution charts, further illustrated the model's accuracy and user sentiment patterns. The study’s findings align with previous research in digital finance, which emphasizes the critical role of user feedback in app development and user retention. However, unique insights regarding the challenges faced by buy-now-pay-later (BNPL) platforms like Kredivo were also observed, notably around customer service and fee transparency. The study highlights the potential of sentiment analysis as a tool for digital finance app developers to continuously improve service quality. Limitations include potential biases in the dataset and model limitations, suggesting future research directions that incorporate additional data sources and advanced NLP models.