Authorship Verification in the Absence of Explicit Features and Thresholds

Halvani, Oren; Graner, Lukas; Vogel, Inna

doi:10.1007/978-3-319-76941-7_34

Cited by 28 publications

(29 citation statements)

References 12 publications

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“…During the last decade, PAN contributed to focus the attention of the research community on specific digital text forensics tasks, built benchmark datasets, and estimated the effectiveness as well as the weaknesses of the state of the art. The developed datasets cover multiple genres and languages while the top-ranked PAN submissions have been used as baselines in subsequent research [12,22]. In addition, the evolution of tasks within PAN made the exploration of new tasks feasible.…”

Section: Discussionmentioning

confidence: 99%

A Decade of Shared Tasks in Digital Text Forensics at PAN

Potthast

Rosso

Stamatatos

et al. 2019

Lecture Notes in Computer Science

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Digital text forensics aims at examining the originality and credibility of information in electronic documents and, in this regard, to extract and analyze information about the authors of these documents. The research field has been substantially developed during the last decade. PAN is a series of shared tasks that started in 2009 and significantly contributed to attract the attention of the research community in well-defined digital text forensics tasks. Several benchmark datasets have been developed to assess the state-of-the-art performance in a wide range of tasks. In this paper, we present the evolution of both the examined tasks and the developed datasets during the last decade. We also briefly introduce the upcoming PAN 2019 shared tasks.

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Section: Discussionmentioning

confidence: 99%

A Decade of Shared Tasks in Digital Text Forensics at PAN

Potthast

Rosso

Stamatatos

et al. 2019

Lecture Notes in Computer Science

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“…The chat conversations stem from a variety of sources including emails and instant messengers (e. g., MSN, AOL or Yahoo), where for each conversation, we ensured that only chat lines from the offender were extracted. We applied the same problem construction procedure as for the corpus C DBLP , which resulted in 1,100 verification 7 https://dblp.uni-trier.de 8 Note that each document is single-authored. 9 For example, repetitions, metaphors, rhetorical questions, oxymorons, etc.…”

Section: Perverted Justice Corpusmentioning

confidence: 99%

Assessing the Applicability of Authorship Verification Methods

Halvani

Winter

Graner

2019

Proceedings of the 14th International Conference on Availability, Reliability and Security

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Authorship verification (AV) is a research subject in the field of digital text forensics that concerns itself with the question, whether two documents have been written by the same person. During the past two decades, an increasing number of proposed AV approaches can be observed. However, a closer look at the respective studies reveals that the underlying characteristics of these methods are rarely addressed, which raises doubts regarding their applicability in real forensic settings. The objective of this paper is to fill this gap by proposing clear criteria and properties that aim to improve the characterization of existing and future AV approaches. Based on these properties, we conduct three experiments using 12 existing AV approaches, including the current state of the art. The examined methods were trained, optimized and evaluated on three self-compiled corpora, where each corpus focuses on a different aspect of applicability. Our results indicate that part of the methods are able to cope with very challenging verification cases such as 250 characters long informal chat conversations (72.7% accuracy) or cases in which two scientific documents were written at different times with an average difference of 15.6 years (> 75% accuracy). However, we also identified that all involved methods are prone to cross-topic verification cases.

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“…Profile‐based methods are better able to handle cases with limited text length since they concatenate all available documents. This paradigm is more popular in recent studies (Ding et al, ; Halvani et al, ; Potha & Stamatatos, ). There are also some attempts to combine instance‐based and profile‐based paradigms (Bagnall, ; Sari & Stevenson, ).…”

Section: Previous Workmentioning

confidence: 99%

“…The latter can be determined by using information from other verification cases (Jankowska et al, ; Potha & Stamatatos, ). A recent study attempts to determine all necessary thresholds without using any additional resources (Halvani, Graner, & Vogel, ). In general, intrinsic methods are very efficient and robust methods, with few parameters to be set, and can be easily applied to any corpus.…”

Section: Previous Workmentioning

confidence: 99%

Improving author verification based on topic modeling

Potha

Stamatatos

2019

Asso for Info Science & Tech

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Authorship analysis attempts to reveal information about authors of digital documents enabling applications in digital humanities, text forensics, and cyber‐security. Author verification is a fundamental task where, given a set of texts written by a certain author, we should decide whether another text is also by that author. In this article we systematically study the usefulness of topic modeling in author verification. We examine several author verification methods that cover the main paradigms, namely, intrinsic (attempt to solve a one‐class classification task) and extrinsic (attempt to solve a binary classification task) methods as well as profile‐based (all documents of known authorship are treated cumulatively) and instance‐based (each document of known authorship is treated separately) approaches combined with well‐known topic modeling methods such as Latent Semantic Indexing (LSI) and Latent Dirichlet Allocation (LDA). We use benchmark data sets and demonstrate that LDA is better combined with extrinsic methods, while the most effective intrinsic method is based on LSI. Moreover, topic modeling seems to be particularly effective for profile‐based approaches and the performance is enhanced when latent topics are extracted by an enriched set of documents. The comparison to state‐of‐the‐art methods demonstrates the great potential of the approaches presented in this study. It is also demonstrates that even when genre‐agnostic external documents are used, the proposed extrinsic models are very competitive.

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Authorship Verification in the Absence of Explicit Features and Thresholds

Cited by 28 publications

References 12 publications

A Decade of Shared Tasks in Digital Text Forensics at PAN

A Decade of Shared Tasks in Digital Text Forensics at PAN

Assessing the Applicability of Authorship Verification Methods

Improving author verification based on topic modeling

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