Abstract
Authorship analysis deals with the identification of authors which is a problem of text data mining and classification. There are numerous techniques and algorithms that have been published so far, in the field of stylometry. In this regard, the primary objective of the present review is to provide the status of the different studies carried out on authorship analysis based on the important research contributions. The authors have mainly focused on each of the article selected for review (2010–16), by summarizing the authorship detection fields, the corpus, the features of authorship analysis, and authorship attribution techniques used which could provide a platform to distinguish between different research contributions and the diverse techniques used in classifying the author's texts. The details on common tools and authorship attribution techniques published in the recent past would be of importance to the concerned researchers as an aid towards text data mining and future growth in the study of authorship attribution.
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