Authorship Attribution Using Word Sequences
نویسندگان
چکیده
Authorship attribution is the task of identifying the author of a given text. The main concern of this task is to define an appropriate characterization of documents that captures the writing style of authors. This paper proposes a new method for authorship attribution supported on the idea that a proper identification of authors must consider both stylistic and topic features of texts. This method characterizes documents by a set of word sequences that combine functional and content words. The experimental results on poem classification demonstrated that this method outperforms most current state-of-the-art approaches, and that it is appropriate to handle the attribution of short documents.
منابع مشابه
More than Word Frequencies: Authorship Attribution via Natural Frequency Zoned Word Distribution Analysis
With such increasing popularity and availability of digital text data, authorships of digital texts can not be taken for granted due to the ease of copying and parsing. This paper presents a new text style analysis called natural frequency zoned word distribution analysis (NFZ-WDA), and then a basic authorship attribution scheme and an open authorship attribution scheme for digital texts based ...
متن کاملSyntactic Stylometry: Using Sentence Structure for Authorship Attribution
Most approaches to statistical stylometry have concentrated on lexical features, such as relative word frequencies or type-token ratios. Syntactic features have been largely ignored. This work attempts to fill that void by introducing a technique for authorship attribution based on dependency grammar. Syntactic features are extracted from texts using a common dependency parser, and those featur...
متن کاملA Profile-Based Authorship Attribution Approach to Forensic Identification in Chinese Online Messages
With the popularity of Internet technologies and applications, inappropriate or illegal online messages have become a problem for the society. The goal of authorship attribution for anonymous online messages is to identify the authorship from a group of potential suspects for investigation identification. Most previous contributions focused on extracting various writing-style features and emplo...
متن کاملReducing Vector Space Dimensionality in Automatic Classification for Authorship Attribution
RESUMEN For automatic classification, the implications of having too many classificatory features are twofold. On the one hand, some features may not be helpful in discriminating classes and should be removed from the classification. On the other hand, redundant features may produce negative effects as their number grows therefore their detrimental impact must be minimized or limited. In text c...
متن کاملAuthorship Attribution Using Word Network Features
In this paper, we explore a set of novel features for authorship attribution of documents. These features are derived from a word network representation of natural language text. As has been noted in previous studies, natural language tends to show complex network structure at word level, with low degrees of separation and scale-free (power law) degree distribution. There has also been work on ...
متن کامل