The term “fake news” has been popularized by Donald Trump, the President of the United States of America, since 2016. Since then studies on “fake news” are booming as there are more than 7,000 academic research articles published in 2016. Yet, a more astonishing fact is that more than 44% of people treat Facebook and the like social media as the ONLY news source. In USA, there are more than 67% people read social media and 20% or more read them very frequently. The most surprising study shows that fake news are more popular than true news, among the top 20 news articles.

The first step to combat “fake news”, obviously is to scrutinize the news itself, for its data quality such as data integrity, authentication, authorization, confidentiality, and privacy etc., as is done by CDO (Chief Data Office). An easiest way to identify “fake news” is to determine the news author, publication source, date, and references. Unfortunately, in social media, such as Line, PTT, and WeChat, those features are almost always missing and are extremely difficult to be identified “automatically”.

TICC (Taiwan Information Care Center) project takes a completely different but maybe the most practical approach. It creates a database such that: it contains the most comprehensive proven fake news, and to fake news checking, with the fastest response, the most accurate, the least un-relevant, and the most timely fake news search results.

TICC will be the best tool for researches on text-based data-mining such as frequent patterns, clustering, classification, and data analytics. TICC is also a key breakthrough for researches with Natural Language Processing (NPL), Artificial Intelligence, Machine Learning, as well as applications to text-intensive, political, sociological, and economical sciences, and law, accounting and liberal arts.