Inference and Disputed Authorship: The Federalist

A NEW book by Mr. Udny Yule is a statistical event which, though of great rarity, is all the more welcome when it occurs. This, however, is not a formal treatment of a subject which has already shaken down into definite lines of development, or even a systematic introduction to such a subject. Rather is it an account in volume form of Mr. Yule's incursion into a novel and interesting field of research. The Statistical Study of Literary Vocabulary By G. Udny Yule. Pp. ix + 306. (Cambridge: At the University Press, 1944.) 25s. net.

The Statistical Study of Literary Vocabulary

The analysis of authorial style, termed stylometry, assumes that style is quantifiably measurable for evaluation of distinctive qualities. Stylometry research has yielded several methods and tools over the past 200 years to handle a variety of challenging cases. This survey reviews several articles within five prominent subtasks: authorship attribution, authorship verification, authorship profiling, stylochronometry, and adversarial stylometry. Discussions on datasets, features, experimental techniques, and recent approaches are provided. Further, a current research challenge lies in the inability of authorship analysis techniques to scale to a large number of authors with few text samples. Here, we perform an extensive performance analysis on a corpus of 1,000 authors to investigate authorship attribution, verification, and clustering using 14 algorithms from the literature. Finally, several remaining research challenges are discussed, along with descriptions of various open-source and commercial software that may be useful for stylometry subtasks.

Surveying Stylometry Techniques and Applications

Compromising legitimate accounts has been the most used strategy to spread malicious content on OSN (Online Social Network). To address this problem, we propose a pure text mining approach to check if an account has been compromised based on its posts content. In the first step, the proposed approach extracts the writing style from the user account. The second step comprehends the k-Nearest Neighbors algorithm (k-NN) to evaluate the post content and identify the user. Finally, Baseline Updating (third step) consists of a continuous updating of the user baseline to support the current trends and seasonality issues of user's posts. Experiments were carried out using a dataset from Twitter composed by tweets of 1000 users. All the three steps were individually evaluated, and the results show that the developed method is stable and can detect the compromised accounts. An important observation is the Baseline Updating contribution, which leads to an enhancement of accuracy superior of 60 %. Regarding average accuracy, the developed method achieved results over 93 %.

Authorship verification applied to detection of compromised accounts on online social networks

Machine Learning Methods for Stylometry: Authorship Attribution and Author Profiling

objective in this paper is to provide a review of the different studies done on authorship analysis. Focus is on outlining the Stylometric features that allow distinguishing between authors and on listing the diverse techniques used to classify an author's texts.

https://research.ijcaonline.org/volume86/number12/pxc3893384.pdf

Ismail Kassou

Papers

Authorship Analysis Studies: A Survey