Constructing a Broad View of Tax Compliance Intentions Based on Big Data

Taxpayer compliance is currently one of the problems faced by the government in any country, especially in developing countries. Taxpayer compliance can be assessed from the intention of the taxpayer toward compliance with the tax itself. The Directorate General of Taxes as an extension of the government in tax matters has the obligation to implement policies and technical standardization in the field of taxation, including in providing efforts to provide an understanding of the importance of taxation in developing a country. Therefore, tax compliance is an important thing to be improved by the government through tax compliance intentions. The basis related to compliance intentions is the Theory of Planned Behavior by (Ajzen in Organ Behav Hum Decis Process 50:179–211, 1991 [1]) which in this case is used as the basis for this discussion. To determine the factors driving the intention to comply, it is necessary to search for any variables that influence this. By using big data, the variables obtained are more in line with the current reality, because they are taken directly from the virtual world, which is more specifically sourced from online media. After the data is mined from social media, the raw data will be extracted and analyzed using Discourse Network Analysis (DNA) to be compiled into a variable which will then be modeled using Structural Equation Modeling (SEM).