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Approaches of Authorship Verification
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 175 - Number 18 |
| Year of Publication: 2020 |
| Authors: Shaimaa Ayman, Mohamed Eisa, Fifi Farouk |
10.5120/ijca2020920692
|
Shaimaa Ayman, Mohamed Eisa, Fifi Farouk . Approaches of Authorship Verification. International Journal of Computer Applications. 175, 18 ( Sep 2020), 11-18. DOI=10.5120/ijca2020920692
Abstract
Nowadays, there are massive amounts of texts in digital form in digital libraries, online journalism, and social networks; for example, Twitter is estimated half a billion tweets are sent out each day. The expanded usage of Online Social Network (OSN) has become necessary to appear to grow of Authorship Verification (AV), OSN is the environment in which users can connect with other users to discuss ideas of any topics then expansion data and information. AV considered as a resource of researches and information in different ways, as is the case Sentiment Analysis (SA). Information that gained from Twitter and Facebook or any other OSN is considered valuable in some areas such as public opinion organizations and online marketing. The crimes also increased over on the internet with textual data. To reduce the problems raised on text through the internet, the researchers have attracted to authorship analysis which is one of the important areas. AV is a type of authorship analysis that is used to verify an author by checking whether the text document is written by the disputed author. The accuracy of AV depends primarily on the features used to distinguish the writing style of documents. In previous works of AV, researchers proposed several types of stylistic features for distinguishing the writing style of the authors. The researchers analyzed that the AV performance was weak when used stylistic features alone in the experiments. Therefore, researchers resorted to more accurate methods that compute the features by using the weight measures. The weight measures calculate the document weights of training, and test documents. Then, the competition between the weights of training document and the weights of test document were implemented; to verify the author of the document.
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