Gender detection and identifying one's handwriting with handwriting analysis

In terms of demographic properties, many statistical and mathematical analyses investigate similar and different variables. Especially, differences regarding gender have become subject to research. Therefore, detecting gender through handwriting can give pace to research in other disciplines. Moreover, the research can be useful in any field where gender detection is needed. This study fulfills two objectives. The first one is to find out whether a writer can identify his/her own handwriting. The second objective is to detect the gender of a writer of a text with the help of graphology and computer sciences. The impact of the study is reflected in the fact that findings can be used in fields where gender detection is needed, and that the detection is done with the help of expert and intelligent systems. At the end of the study, gender detection was performed for the individuals by making use of 133 attributes. Then, a decision tree and lists of rules were created with some algorithms. The purpose was to detect the gender of the person by making a character analysis of the handwriting with the help of decision tree formation methods in data mining. The analysis showed that it is possible to detect the gender of a person with the use of the specified attributes. The study reached a success level of 93.75% with ID3 algorithm.