Analisis Sentimen Pengungkapan Informasi Manajemen: Text Mining Berbasis Metode VADER - Emelia Aprodaid Marwa; Ari Budi Kristanto (Owner : Riset dan Jurnal Akuntansi, 2022)
Financial statements present information related to the firm’s financial condition. However, there is various types of data are provided to help us in assessing and understanding the firm’s business condition. The most abundant firm-related data that are available are in the form of text. It can include annual reports, official websites, or even social media posts that may contain non-financial data. Nonfinancial information is also important to help the interpretation of financial information. The research aims to analyze the sentiment of management discussion and analysis included in the manufacturing company's annual report. The research sample is manufacturing companies listed on the Indonesia Stock Exchange (IDX) during the 2016-2020 period in a row. There are 102 companies or 510 research observations include in this research. This research uses a sentiment analysis technique based on a lexicon-based approach using the VADER method. Meanwhile, the sentiment analysis process will be assisted by the Orange Data Mining application. The results of the research show that positive disclosure is greater than negative sentiments. The pattern of sentiment for companies that are classified based on sector, company size (total assets and total sales), profitability (ROI), and liquidity (current ratio) shows relatively the same results. These results illustrate that company characteristics do not make a difference in the choice of word sentiment in manufacturing companies.