Efstathios Stamatatos

• University of the Aegean

The paper gives a brief overview of the four shared tasks organized at the PAN 2024 lab on digital text forensics and stylometry to be hosted at CLEF 2024. The goal of the PAN lab is to advance the state-of-the-art in text forensics and stylometry through an objective evaluation of new and established methods on new benchmark datasets. Our four tas...

The paper gives a brief overview of three shared tasks which have been organized at the PAN 2023 lab on digital text forensics and stylometry hosted at the CLEF 2023 conference. The tasks include authorship verification across discourse types, multi-author writing style analysis, profiling cryptocurrency influencers with few-shot learning, and trig...

The paper gives a brief overview of the four shared tasks organized at the PAN 2023 lab on digital text forensics and stylometry to be hosted at the CLEF 2023 conference. The general goal of the PAN lab is to advance the state-of-the-art in text forensics and stylometry while ensuring objective evaluation of new and established methods on newly dev...

The paper gives a brief overview of three shared tasks which have been organized at the PAN 2022 lab on digital text forensics and stylometry hosted at the CLEF 2022 conference. The tasks include authorship verification across discourse types, multi-author writing style analysis and author profiling. Some of the tasks continue and advance past edit...

The paper gives a brief overview of the four shared tasks to be organized at the PAN 2022 lab on digital text forensics and stylometry hosted at the CLEF 2022 conference. The tasks include authorship verification across discourse types, multi-author writing style analysis, author profiling, and content profiling. Some of the tasks continue and adva...

Idiosyncrasies in human writing styles make it difficult to develop systems for authorship identification that scale well across individuals. In this year's edition of PAN, the authorship identification track focused on open-set authorship verification, so that systems are applied to unknown documents by previously unseen authors in a new domain. A...

The paper gives a brief overview of the three shared tasks organized at the PAN 2021 lab on digital text forensics and stylometry hosted at the CLEF conference. The tasks include authorship verification across domains, author profiling for hate speech spreaders, and style change detection for multi-author documents. In part the tasks are new and in...

Authorship attribution attempts to identify the authors behind texts and has important applications mainly in digital forensics, cyber-security, digital humanities, and social media analytics. A challenging yet realistic scenario is cross-domain attribution where texts of known authorship (training set) differ from texts of disputed authorship (tes...

The paper gives a brief overview of the three shared tasks to be organized at the PAN 2021 lab on digital text forensics and stylometry hosted at the CLEF conference. The tasks include authorship verification across domains, author profiling for hate speech spreaders, and style change detection for multi-author documents. In part the tasks are new...

When writing source code, programmers have varying levels of freedom when it comes to the creation and use of identifiers. Do they habitually use the same identifiers, names that are different to those used by others? Is it then possible to tell who the author of a piece of code is by examining these identifiers? If so, can we use the presence or a...

Authorship identification remains a highly topical research problem in computational text analysis with many relevant applications in contemporary society and industry. For this edition of PAN, we focused on authorship verification , where the task is to assess whether a pair of documents has been authored by the same individual. Like in previous e...

We briefly report on the four shared tasks organized as part of the PAN 2020 evaluation lab on digital text forensics and authorship analysis. Each tasks is introduced, motivated, and the results obtained are presented. Altogether, the four tasks attracted 230 registrations, yielding 83 successful submissions. This, and the fact that we continue to...

Authorship attribution attempts to identify the authors behind texts and has important applications mainly in cyber-security, digital humanities and social media analytics. An especially challenging but very realistic scenario is cross-domain attribution where texts of known authorship (training set) differ from texts of disputed authorship (test s...

The prerequisite of many approaches to authorship analysis is a representation of writing style. But despite decades of research, it still remains unclear to what extent commonly used and widely accepted representations like character trigram frequencies actually represent an author's writing style, in contrast to more domain-specific style compone...

Author verification is a fundamental problem in authorship attribution, and it suits most relevant applications where it is not possible to predefine a closed set of suspects. So far, the most successful approaches attempt to sample the non-target class (all documents by all other authors) and transform author verification to a binary classificatio...

The paper gives a brief overview of the four shared tasks that are to be organized at the PAN 2020 lab on digital text forensics and stylometry, hosted at CLEF conference. The tasks include author profiling, celebrity profiling, cross-domain author verification, and style change detection, seeking to advance the state of the art and to evaluate it...

The facilities provided by social media and computer-mediated communication make easy the dissemination of deceptive behavior, after which different entities or people could be affected. The deception detection by supervised learning has been widely studied; however, the scenario in which there is one domain of interest and the labeled data is in a...

PAN is a networking initiative for digital text forensics, where researchers and practitioners study technologies for text analysis with regard to originality, authorship, and trustworthiness. The practical importance of such technologies is obvious for law enforcement, cyber-security, and marketing, yet the general public needs to be aware of thei...

We briefly report on the four shared tasks organized as part of the PAN 2019 evaluation lab on digital text forensics and authorship analysis. Each task is introduced, motivated, and the results obtained are presented. Altogether, the four tasks attracted 373 registrations, yielding 72 successful submissions. This, and the fact that we continue to...

Several methods have been proposed for determining plagiarism between pairs of sentences, passages or even full documents. However, the majority of these methods fail to reliably detect paraphrase plagiarism due to the high complexity of the task, even for human beings. Paraphrase plagiarism identification consists in automatically recognizing docu...

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 significant...

Web genre identification can boost information retrieval systems by providing rich descriptions of documents and enabling more specialized queries. The open-set scenario is more realistic for this task as web genres evolve over time and it is not feasible to define a universally agreed genre palette. In this work, we bring to bear a novel approach...

Author verification is a fundamental task in authorship analysis and associated with significant applications in humanities, cyber-security, and social media analytics. In some of the relevant studies, there is evidence that heterogeneous ensembles can provide very reliable solutions, better than any individual verification model. However, there is...

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 sys...

Web genre detection is a task that can enhance information retrieval systems by providing rich descriptions of documents and enabling more specialized queries. Most of previous studies in this field adopt the closed-set scenario where a given palette comprises all available genre labels. However this is not a realistic setup since web genres are co...

PAN 2018 explores several authorship analysis tasks enabling a systematic comparison of competitive approaches and advancing research in digital text forensics. More specifically, this edition of PAN introduces a shared task in cross-domain authorship attribution, where texts of known and unknown authorship belong to distinct domains, and another t...

Author verification is a fundamental task in authorship analysis and associated with important applications in humanities and forensics. In this paper, we propose the use of an intrinsic profile-based verification method that is based on latent semantic indexing (LSI). Our proposed approach is easy-to-follow and language independent. Based on exper...

In recent years, one of the two fully preserved ancient Greek tragic plays of disputed authorship, Rhesus, traditionally attributed to Euripides, has been the object of a quite lively scholarly interest. The rather extreme number, for the standards of classical philology, of four published commentaries in 10 years, by Athanasios D. Stefanis, [Eurip...

The effectiveness of character n-gram features for representing the stylistic properties of a text has been demonstrated in various independent Authorship Attribution (AA) studies. Moreover, it has been shown that some categories of character n-grams perform better than others both under single and cross-topic AA conditions. In this work, we presen...

Authorship attribution attempts to reveal the authors of documents. In recent years, research in this field has grown rapidly. However, the performance of state-of-the-art methods is heavily affected when text of known authorship and texts under investigation differ in topic and/or genre. So far, it is not clear how to quantify the personal style o...

In this paper, we describe an approach to create a summary obfuscation corpus for the task of plagiarism detection. Our method is based on information from the Document Understanding Conferences related to years 2001 and 2006, for the English language. Overall, an unattributed summary used within someone else’s document is considered a kind of plag...

Authorship verification has gained a lot of attention during the last years mainly due to the focus of PAN@CLEF shared tasks. A verification method called Impostors, based on a set of external (impostor) documents and a random subspace ensemble, is one of the most successful approaches. Variations of this method gained top-performing positions in r...

The PAN 2017 shared tasks on digital text forensics were held in conjunction with the annual CLEF conference. This paper gives a high-level overview of each of the three shared tasks organized this year, namely author identification, author profiling, and author obfuscation. For each task, we give a brief summary of the evaluation data, performance...

The effectiveness of character n-gram features for representing the stylistic properties of a text has been demonstrated in various independent Authorship Attribution (AA) studies. Moreover, it has been shown that some categories of character n-grams perform better than others both under single and cross-topic AA conditions. In this work, we presen...

This paper presents an overview of the PAN/CLEF evaluation lab. During the last decade, PAN has been established as the main forum of digital text forensic research. PAN 2016 comprises three shared tasks: (i) author identification, addressing author clustering and diarization (or intrinsic plagiarism detection); (ii) author profiling, addressing ag...

The veil of anonymity provided by smartphones with pre-paid SIM cards, public Wi-Fi hotspots, and distributed networks like Tor has drastically complicated the task of identifying users of social media during forensic investigations. In some cases, the text of a single posted message will be the only clue to an author's identity. How can we accurat...

The style of documents is an important property that can be used as discriminant factor in text mining applications. Among the great number of possible measures proposed to quantify writing style there are some features that can be characterized as universal, in the sense that they can be easily extracted from any kind of text in practically any na...

In this paper, we revisit author identification research by conducting a new kind of large-scale reproducibility study: we select 15 of the most influential papers for author identification and recruit a group of students to reimplement them from scratch. Since no open source implementations have been released for the selected papers to date, our p...

This paper presents an overview of the author identification task at PAN-2015 evaluation lab. Similar to previous editions of PAN, this shared task focuses on the problem of author verification: given a set of documents by the same author and another document of unknown authorship, the task is to determine whether or not the known and unknown docum...

This paper presents an overview of the PAN/CLEF evaluation lab. During the last decade, PAN has been established as the main forum of text mining research focusing on the identification of personal traits of authors left behind in texts unintentionally. PAN 2015 comprises three tasks: plagiarism detection, author identification and author profiling...

Genre detection of web documents fits an open-set classification task. The web documents not belonging to any predefined genre or where multiple genres co-exist is considered as noise. In this work we study the impact of noise on automated genre identification within an open-set classification framework. We examine alternative classification models...

The Author Profiling (AP) task aims to reveal as much as possible information from a given author’s document (e.g., age, gender, etc.). AP is crucial for several applications, ranging from customized advertising to computer forensics, psychology, and entertainment. Nonetheless, the AP task is far from being solved, particularly in social media doma...

This paper reports on the PAN 2014 evaluation lab which hosts three shared tasks on plagiarism detection, author identification, and author profiling. To improve the reproducibility of shared tasks in general, and PAN’s tasks in particular, the Webis group developed a new web service called TIRA, which facilitates software submissions. Unlike many...

Authorship verification is one of the most challenging tasks in style-based text categorization. Given a set of documents, all by the same author, and another document of unknown authorship the question is whether or not the latter is also by that author. Recently, in the framework of the PAN-2013 evaluation lab, a competition in authorship verific...

We present a work on detection of manual paraphrasing in documents in comparison with a set of source documents. Manual paraphrasing is a realistic type of plagiarism, where the obfuscation is introduced manually in documents. We have used PAN-PC-10 data set to develop and evaluate our algorithm. The proposed approach consists of two steps, namely,...

In this paper we introduce and discuss a concept of syntactic n-grams (sn-grams). Sn-grams differ from traditional n-grams in the manner how we construct them, i.e., what elements are considered neighbors. In case of sn-grams, the neighbors are taken by following syntactic relations in syntactic trees, and not by taking words as they appear in a te...

The author identification task at PAN-2014 focuses on author verification. Similar to PAN-2013 we are given a set of documents by the same author along with exactly one document of questioned authorship, and the task is to determine whether the known and the questioned documents are by the same author or not. In comparison to PAN-2013, a significan...

This paper outlines the concepts and achievements of our evaluation lab on digital text forensics, PAN 13, which called for original research and development on plagiarism detection, author identification, and author profiling. We present a standardized evaluation framework for each of the three tasks and discuss the evaluation results of the altog...

Ruling line removal is an important pre-processing step in document image processing. Several algorithms have been proposed for this task. However, it is important to be able to take full advantage of the existing algorithms by adapting them to the specific properties of a document image collection. In this paper, a system is presented, appropriate...

Automated Genre Identification (AGI) of web pages is a problem of increasing importance since web genre (e.g. blog, news, e-shops, etc.) information can enhance modern Information Retrieval (IR) systems. The state-of-the-art in this field considers AGI as a closed-set classification problem where a variety of web page representation and ma-chine le...

The constantly increasing amount of opinionated texts found in the Web had a significant impact in the development of sentiment analysis. So far, the majority of the comparative studies in this field focus on analyzing fixed (offline) collections from certain domains, genres, or topics. In this paper, we present an online system for opinion mining...

The paper introduces and discusses a concept of syntactic n-grams (sn-grams) that can be applied instead of traditional n-grams in many NLP tasks. Sn-grams are constructed by following paths in syntactic trees, so sn-grams allow bringing syntactic knowledge into machine learning methods. Still, previous parsing is necessary for their construction....

Automated Genre Identification (AGI) of web pages is a problem of increasing importance since web genre (e.g. blog, news, e-shops, etc.) information can enhance modern Information Retrieval (IR) systems. The state-of-the-art in this field considers AGI as a closed-set classification problem where a variety of web page representation and machine lea...

The author identification task at PAN-2013 focuses on author verification where given a set of documents by a single author and a questioned document, the problem is to determine if the questioned document was written by that particular author or not. In this paper we present the evaluation setup, the performance measures, the new corpus we built f...

The discovery of web documents about certain topics is an important task for web-based applications including web document retrieval, opinion mining and knowledge extraction. In this paper, we propose an agent-based focused crawling framework able to retrieve topic- and genre-related web documents. Starting from a simple topic query, a set of focus...

Similarly to natural language texts, source code documents can be distinguished by their style. Source code author identification can be viewed as a text classification task given that samples of known authorship by a set of candidate authors are available. Although very promising results have been reported for this task, the evaluation of existing...

In this paper we introduce a concept of syntactic n-grams (sn-grams). Sn-grams differ from traditional n-grams in the manner of what elements are considered neighbors. In case of sn-grams, the neighbors are taken by following syntactic relations in syntactic trees, and not by taking the words as they appear in the text. Dependency trees fit directl...

The vast amount of user-generated content on the Web has increased the need for handling the problem of automatically processing content in web pages. The segmentation of web pages and noise (non-informative segment) removal are important pre-processing steps in a variety of applications such as sentiment analysis, text summarization and informatio...

In this paper a novel method for detecting plagiarized passages in document collections is presented. In contrast to previous work in this field that uses content terms to represent documents, the proposed method is based on a small list of stopwords (i.e., very frequent words). We show that stopword n-grams reveal important information for plagiar...

In this paper a novel method for detecting plagiarized passages in document collections is presented. In contrast to previous work in this field that uses mainly content terms to represent documents, the proposed method is based on structural information provided by occurrences of a small list of stopwords (i.e., very frequent words). We show that...

The Fourth International Workshop on Uncovering Plagiarism, Authorship, and Social Software Misuse (PAN10) was held in conjunction with the 2010 Conference on Multilingual and Multimodal Information Access Evaluation (CLEF-10) in Padua, Italy. The workshop was organized as a competition covering two tasks: plagiarism detection and Wikipedia vandali...

When writing source code, programmers have varying levels of freedom when it comes to the creation and use of identifiers. Do they habitually use the same identifiers, names that are different to those used by others? Is it then possible to tel I who the author of a piece of code is by examining these identifiers? If so, can we use the presence or...

Plagiarism is widely acknowledged to be a significant and increasing problem for higher education institutions (McCabe 2005; Judge 2008). A wide range of solutions, including several commercial systems, have been proposed to assist the educator in the ...

Author identification models fall into two major categories according to the way they handle the training texts: profile-based models produce one representation per author while instance-based models produce one representation per text. In this paper, we propose an approach that combines two well-known representatives of these categories, namely th...

Nowadays, in a wide variety of situations, source code authorship identification has become an issue of major concern. Such situations include authorship disputes, proof of authorship in court, cyber attacks in the form of viruses, trojan horses, logic bombs, fraud, and credit card cloning. Source code author identification deals with the task of i...

Webpages are mainly distinguished by their topic (e.g., politics, sports etc.) and genre (e.g., blogs, homepages, e-shops, etc.). Automatic detection of webpage genre could considerably enhance the ability of modern search engines to focus on the requirements of the user’s information need. In this paper, we present an approach to webpage genre det...

In constraint programming there are often many choices re- garding the propagation method to be used on the constraints of a problem. However, simple constraint solvers usually only apply a stan- dard method, typically (generalized) arc consistency, on all constraints throughout search. Advanced solvers additionally allow for the modeler to choose...

Authorship attribution supported by statistical or computational methods has a long history starting from the 19th century and is marked by the seminal study of Mosteller and Wallace (1964) on the authorship of the disputed “Federalist Papers.” During the last decade, this scientific field has been developed substantially, taking advantage of resea...

The task of intrinsic plagiarism detection deals with cases where no reference corpus is available and it is exclusively based on stylistic changes or inconsistencies within a given document. In this paper a new method is presented that attempts to quantify the style variation within a document using character n-gram profiles and a style change fun...

Authorship identification can be viewed as a text categorization task. However, in this task the most frequent features appear to be the most important discriminators, there is usually a shortage of training texts, and the training texts are rarely evenly distributed over the authors. To cope with these problems, we propose tensors of second order...

The use of Source Code Author Profiles (SCAP) represents a new, highly accurate approach to source code authorship identification that is, unlike previous methods, language independent. While accuracy is clearly a crucial requirement of any author identification method, in cases of litigation regarding authorship, plagiarism, and so on, there is al...

Authorship analysis of electronic texts assists digital forensics and anti-terror investigation. Author identification can be seen as a single-label multi-class text categorization problem. Very often, there are extremely few training texts at least for some of the candidate authors or there is a significant variation in the text-length among the a...

Author identification is a text categorization task with applications in intelligence, criminal law, computer forensics, etc. Usually, in such cases there is shortage of training texts. In this paper, we propose the use of second order tensors for representing texts for this problem, in contrast to the traditional vector space model. Based on a gen...

The increasing number of unsolicited e-mail messages (spam) reveals the need for the development of reliable anti-spam filters. The vast majority of content-based techniques rely on word-based representation of messages. Such approaches require reliable tokenizers for detecting the token boundaries. As a consequence, a common practice of spammers i...

Goal of the workshop was to bring together experts and prospective researchers around the exciting and future-oriented topic of plagiarism analysis, authorship identification, and high similarity search. This topic receives increasing attention, which results, among others, from the fact that information about nearly any subject can be found on the...

An important factor for discriminating between Web pages is their genre (e.g., blogs, personal homepages, e-shops, online newspapers, etc). Web page genre identification has a great potential in information retrieval since users of search engines can combine genre-based and traditional topic-based queries to improve the quality of the results. So f...

This paper deals with the problem of author identification. The common N-grams (CNG) method [6] is a language-independent profile-based approach with good results in many author identification experiments so far. A variation of this approach is presented based on new distance measures that are quite stable for large profile length values. Special e...

Source code author identification deals with identifying the most likely author of a computer program, given a set of predefined author candidates. There are several scenarios where digital evidence of this kind plays a role in investigation and adjudication, such as code authorship disputes, intellectual property infringement, tracing the source o...

Author identification can be seen as a single-label multi-class text categorization problem. Very often, there are extremely few training texts at least for some of the candidate authors or there is a significant variation in the text-length among the available training texts of the candidate authors. Moreover, in this task usually there is no simi...

Authorship attribution can assist the criminal investigation procedure as well as cybercrime analysis. This task can be viewed as a single-label multi-class text categorization problem. Given that the style of a text can be represented as mere word frequencies selected in a language-independent method, suitable machine learning techniques able to d...

Automatic authorship identification offers a valuable tool for supporting crime investigation and security. It can be seen as a multi-class, single-label text categorization task. Character n-grams are a very successful approach to represent text for stylistic purposes since they are able to capture nuances in lexical, syntactical, and structural l...

Source code author identification deals with the task of identifying the most likely author of a computer program, given a set of predefined author candidates. This is usually. based on the analysis of other program samples of undisputed authorship by the same programmer. There are several cases where the application of such a method could be of a...

Source code author identification deals with the task of identifying the most likely author of a computer program, given a set of predefined author candidates. This is usually .based on the analysis of other program samples of undisputed authorship by the same programmer. There are several cases where the application of such a method could be of a...

It is common for libraries to provide public access to historical and ancient document image collections. It is common for such document images to require specialized processing in order to remove background noise and become more legible. In this paper, we propose a hybrid binarization approach for improving the quality of old documents using a com...

This paper presents a content-based approach to spam detection based on low-level information. Instead of the traditional 'bag of words' repre- sentation, we use a 'bag of character n-grams' representation which avoids the sparse data problem that arises in n-grams on the word-level. Moreover, it is language-independent and does not require any lem...

Authorship identification can be seen as a single-label multi-class text categorization problem. Very often, there are extremely few training texts at least for some of the candidate authors. In this paper, we present methods to handle imbalanced multi-class textual datasets. The main idea is to segment the training texts into sub-samples according...

In this paper, we present a binarization technique specifically designed for historical document images. Existing methods for this problem focus on either finding a good global threshold or adapting the threshold for each area so that to remove smear, strains, uneven illumination etc. We propose a hybrid approach that first applies a global thresho...

Source code authorship analysis is the particular field that attempts to identify the author of a computer program by treating each program as a linguistically analyzable entity. This is usually based on other undisputed program samples from the same author. There are several cases where the application of such a method could be of a major benefit,...

This article addresses the problem of identifying the most likely music performer, given a set of performances of the same piece by a number of skilled candidate pianists. We propose a set of very simple features for representing stylistic characteristics of a music performer, introducing ‘norm-based’ features that relate to a kind of ‘average’ per...

This paper deals with the discrimination between machine-printed and handwritten text, a prerequisite for many OCR applications. An easy-to-follow approach is proposed based on an integrated system able to localize text areas and split them in text-lines. A set of simple structural characteristics that capture the differences between machine-printe...