Big Data กับการต่อต้านการทุจริต: กรณีศึกษาข้อมูลการใช้งานโทรศัพท์มือถือ

บทคัดย่อ

The objectives of this academic article are (1) to study how to apply big data generated by mobile phone usages for anti-corruption in Thailand (2) to analyze data and the technique of presenting these big data generated by mobile phone usages in a suitable manner for anti-corruption (3) to propose a practical guideline for big data that can be applied to anti-corruption. The results of this study are that there are 2 types of mobile phone data that can be applied the big data technique: the registration data and usages data. The big data technique such as Classification was then applied to the collected data by using attributed and blacklist information feed from the National Anti-Corruption Commission (NACC) to build a list of suspected users who has the high tendency to corrupt. Applying the Outlier Detection technique into data usage of mobile phone, the corruption can be predicted by analyzing call history, location of the callers, abnormal phone and data usage pattern. First suggestions, public agencies need to have knowledgeable personnel about big data and to build this big data in a secure manner and for the system is able to share data with other related public agencies by providing a method to synchronize between internal and external agencies as needed, once deployed the system could also be extended to detect digital finances corruption. As the system will involve analyzing and collection of personal citizen data, there is a very real potential for exposure therefore, the study propose that strict lawful interception law and related regulation will need to be put in place prior to any deployment, in order to limit violation to citizen privacy. Thereby more digitalization brings to creating a universally accepted transparent and independently verifiable system that will help reduce corruption long term in Thailand. (More Digitalization, Less Corruption)