Digital Humanity and its functionality
As the name digital humanity suggest, digital humanity is an intersection between computational technology and humanities. Then we might wonder, what is humanities? Humanities is a field of studying human cultures. The combine of using technology to study human culture is therefore what digital humanity is. How is Digital Humanity used? One example of it is that we collected a lot of data sets from culture studies, and we data mining the data and extract useful information from the culture data. The process of using technology to analyze culture relative subjects is Digital Humanity. Then why do we need Digital Humanity? Why is it so different? Since the expansion of computer, many things have changed. Traditionally humanity is studied through qualitative analysis of the subject of matter, often times reading books are involved in the analysis of the subject. But nowadays, more and more quantified data can be collected through human interaction. It became apart from the traditional way of studying humanities. The use of technology to derive meaning out of humanities is essential in analyzing humanities.
One way of incorporating the tradictional text- analytic techniques is by using Geographic Information System(GIS) which we learned about in class. GIS is a system which used to present all sorts of data that is relevant to geographic. By using GIS, people can look at different information about the geographic location of interest. By having GIS, researchers can save a lot time resource and obtain relevant information much quicker.
The key methods of DH are Parsing, Machine Translation, Topic categorization and Machine learning (Wikipedia): Parsing are widely applied in writing in computer. Parsing is done by analyzing the relationships between different vocabularies and human thoughts. Automated parsing is a result of quantify narrative analysis, it involved in many application of linear algebra and use algorithm to pair different words by using the interaction of many possibilities, at the end it rank the possibilities and produce possible outcome. The process commonly involved in analyzing big data using machine learning and artificial intelligent.
However, the use of DH has many criticisms. Since the way data is collected have many shortcomings. For example, it is hard to know what types of people the data is collected from. As a result, the issue of sexuality and other social science and political aspect may rise when driving a conclusion from the data.
DH is indeed a very useful tool in doing things that we traditionally cannot achieve. By being able oversee the short coming of DH, we need to be more cautious about the results obtained from the DH analysis and interpret them with an open mind.