Text Reuse Research Articles

Mono-lingual text reuse detection for the Urdu language at lexical level

Text reuse is the process of creating new texts from pre-existing ones. In recent years, Urdu Text Reuse Detection (U-TRD) has garnered the attention of researchers due to the ready availability of digital text all over the internet, which can be copied or paraphrased from other sources without proper attribution, making it easier to reuse but challenging to detect. Previous studies have explored the issue of U-TRD at the phrasal, sentence/passage, and document levels, using benchmark corpora and methods. However, the problem of U-TRD has not been investigated at the lexical level in terms of corpora and methods. To address this research gap, our study has developed a large benchmark corpus manually annotated at the lexical level. This corpus consists of 22,184 text pairs categorized into two levels of rewrite: (1) Derived (8,660) and (2) Non-Derived (13,524). Additionally, our research has involved the development, application, evaluation, and comparison of a range of methods, including baseline methods (uni-gram overlap and word embedding-based methods), along with state-of-the-art transformer-based methods and feature-fusion-based methods, using the proposed UTRD-Lex-23 corpus. Our study concludes that one of our proposed feature-fusion methods outperforms all other methods. The model we propose, which combines seven different Sentence Transformers (ST) (each producing 768 dimension vectors) with one uni-gram (at word level) and sixteen different features extracted from four different Word Embedding (WE) based models (yielding 300 dimension vectors), achieves an F1 score of 0.70601 using 10-fold cross validation. To foster and promote research in Urdu (a low-resourced language) proposed corpus will be freely and publicly available for research purposes.

Minha Terra Tem ____________: Patterns of Text Reuse in “Song of Exile” and its Intertexts

A foundational text of Brazilian Romanticism, Antônio Gonçalves Dias’s “Canção do Exílio,” written in Coimbra (1843) and published in Niterói (1846), is uniquely positioned as Brazil’s most imitated poem. Based on a data set of 500 intertexts spanning the years 1846-2015, this study contemplates the nature of textual borrowing found in the poem’s variations. Looking beyond words shared across texts to the syntactic patterns at play, this paper defines and discusses in detail the concept of Syntactic Templates, develops an algorithm for their identification and considers their utility for understanding this specific text reuse problem.

Crediting Invisible Work: Congress and the Lawmaking Productivity Metric (LawProM)

Congressional observers have long been interested in the distinction between legislative “workhorses” and “showhorses.” However, when scholars operationalize this by measuring legislator productivity, they often neglect many realities of modern lawmaking by focusing on the traditional bill sponsorship and passage process. To better align measurement with practice, we compile widely available data on bill sponsorship, cosponsorship, and amendments; we also use text-as-data methods to credit instances of behind-the-scenes lawmaking via text reuse between bills. We weight achievements from each of these lawmaking methods to create the Lawmaking Productivity Metric for House Members of the 101–113th Congresses. Including methods of lawmaking beyond bill sponsorship provides important insights about who the congressional workhorses are. In particular, we find that traditional measures systematically undercount the legislative successes of women and likely Black Members of Congress because they disproportionately legislate in less visible ways.

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Sewing Pouch on the Run: Lenngren, Text Reuse, and Recontextualizations This article is tracing a newspaper poem, originally published in 1795 in the section for lost and found, and reprinted repeatedly in newspapers in the nineteenth and early twentieth century. The poem describes a girl who has lost a pouch with her sewing kit on a walk through Stockholm. The one who returns it is promised two sugar breads and a kiss as a reward. It was published anonymously but Anna Maria Lenngren was later identified as the author. Following the poem from paper to paper reveals a network of text reuse where texts were borrowed, edited and recontextualized. Several papers all around Sweden published the verse as an anonymous advertisement from 1837 to 1868. Yet, among other things, the editors also changed the place name mentioned in the poem to make it seem as if it was written by a local girl. Another version of the text was widely circulated in papers from 1887 to 1917. This version was truer to the original wording of the poem, but it was published along with an anecdote identifying Lenngren herself as the girl in the text, making it part of her own marriage proposal. This time the poem was placed in the section for humorous titbits, among gossip and funny stories. The different versions of the poem illustrate how newspapers could function as a medium for literature in the nineteenth century. The practice of text reuse had the potential of maximizing the readership but could also mean that authors lost control over their words. When poems became “fugitive verses” in the network of newspapers, they entered a fluid state where authorships were destabilized and texts were recontextualized to fit on the newspaper page.

Neither Corpus Nor Edition: Building a Pipeline to Make Data Analysis Possible on Medieval Arabic Commentary Traditions

We have built a suite of tools in Python to proficiently analyze text reuse and intertextuality for a specific kind of set of medieval Arabic texts (commentaries) available in print. We take these printed editions, scan them, pre-process the images, give it to an OCR engine, clean the results, and store it in a data structure that mimics the explicit intertextual relation the texts have, and continue to perform data analysis on it. Digital approaches to medieval Arabic texts have either been at the micro-level in what has become known as a ‘digital edition’, i.e. the digital representation of one text, densely annotated, most commonly in TEI-XML, or it has been done at the macro-level in what is called a ‘digital corpus’, consisting of thousands of loosely encoded and sparsely annotated plain text files, accompanied by an entire infrastructure and high-performing software to perform broadly scoped queries. The micro-level generally is at the level of tens of thousands of words while the macro-level can be at the level of over a billion words. The micro-level is explicitly designed to be human readable first, while the macro-level is built to be machine readable first. At the micro-level, every little detail needs to be correct and in order, while at the macro-level a fairly large margin of error is still negligible as a mere rounding error. Amidst these levels we have been seeking a meso-level of digital analysis: neither edition nor corpus, but rather a group of texts at the level of hundreds of thousands to millions of words, with a small but perceptible margin of error, and a light but noticeable level of annotations, principally geared towards machine readability, but with ample opportunity for visual inspection and manual correction. In this paper we explain the rationale for our approach, the technical achievements it has led us to, and the results we so far obtained.

Textuality as amplification: reconsidering close reading and distant reading in cultural history

ABSTRACT This article discusses the idea of distant reading and explores the ways in which it can be conducted in research. It focuses especially on how distant reading can contribute to the study of cultural history, which is often regarded as a domain of close reading. The article argues that distant reading methods can successfully be applied in the analysis of cultural transmission in the past, where it is often essential to combine the study of textual signification with the idea of textuality as material flow. The article draws on an example from press history and especially discusses text reuse detection as a strategy for identifying textual amplification.

Not just rubber-stamping: understanding the amending role of the Chinese legislature with bill text reuse

ABSTRACT Recent work challenging the “rubber stamp” view of authoritarian legislatures demonstrate that they are important arenas for policymaking. Yet their amending function remains understudied. To what extent is draft legislation modified in authoritarian parliaments? Why are some bills amended more than others? This article addresses these questions in the Chinese case, using a dataset covering 167 bills adopted by the National People's Congress or its Standing Committee from 2008 to 2022. I assess the degree of bill change by comparing bill content before and after parliamentary treatment with a text reuse method. Results show a moderately high level of amendment activity, with noticeable variations across bills. I argue that the amending role of the Chinese legislature serves a crucial mechanism for integrating and coordinating bureaucratic interests. I find that bills are modified to a greater extent if more ministerial and provincial stakeholders are involved within the legislative arena. This article provides systemic evidence supporting the power-sharing theory: legislative institutions compensate for the executive-level deficiencies and help manage intra-elite relations in policymaking. It does not confirm the influence of public opinion, casting doubt on the bottom-up account of bill change.

Transparent generosity. Introducing the impresso interface for the exploration of semantically enriched historical newspapers

Semantically enriched historical newspapers offer a multitude of opportunities for data-driven exploration and analysis. In this paper we introduce the impresso interface which integrates several types of semantic enrichments and data visualization and thereby supports new exploratory workflows and the critical assessment of large-scale digitized source collections. The interface targets historians and integrates search, filtering, comparison, and recommendation based on automatically detected topics, linked named entities, text reuse, n-grams, image similarity, language, and OCR quality. We introduce the theoretical principles which guided interface development and reflect on the user requirements gathering process together with a case-study driven exemplification of novel workflows facilitated by the interface. We conclude with an overview of accompanying educational materials and discuss results from a user evaluation.

Documentary Formulae as Text Reuse Templates: <i>Constat</i> and <i>Manifestus</i> Clauses in Early Medieval Latin Charters

This paper seeks to develop a digital diplomatic approach for reducing medieval charters’ documentary formulae into text reuse templates that represent their variational subtypes. The paper also tests this approach by visualizing the variation of two, partly mutually competing, formulae. The research data consists of 1,024 constat and manifestus clauses extracted from Latin charters written in Tuscany in the eighth to tenth centuries. Charters largely consist of formulae, which are prefabricated semi-fixed expressions of juridical content and recur in varying forms in charters of the same type. The complex interplay of documentary text reuse elements in time and place can be used to investigate historical drifts of documentary production and underlying administrative and cultural changes. The computer-assisted text reuse approach proposed is expected to be applicable to large datasets and scalable to other historical contexts. 

A Comparative text similarity analysis of the works of Bernard Mandeville

Text similarity analysis entails studying identical and closely similar text passages across large corpora, with a particular focus on intentional and unintentional borrowing patterns. At a larger scale, detecting repeated passages takes on added importance, as the same text can convey different meanings in different contexts. This approach offers numerous benefits, enhancing intellectual and literary scholarship by simplifying the identification of textual overlaps. Consequently, scholars can focus on the theoretical aspects of reception with an expanded corpus of evidence at their disposal. This article adds to the expanding field of historical text reuse, applying it to intellectual history and showcasing its utility in examining reception, influence, popularity, authorship attribution, and the development of tools for critical editions. Focused on the works and various editions of Bernard Mandeville (1670–1733), the research applies comparative text similarity analysis to explore his borrowing habits and the reception of his works. Systematically examining text reuses across several editions of Mandeville’s works, it provides insights into the evolution of his output and influences over time. The article adopts a forward-looking perspective in historical research, advocating for the integration of archival and statistical evidence. This is illustrated through a detailed examination of the attribution of Publick Stews to Mandeville. Analysing cumulative negative evidence of borrowing patterns suggests that Mandeville might not have been the author of the piece. However, the article aims not to conclude the debate but rather to open it up, underscoring the importance of taking such evidence into consideration. Additionally, it encourages scholars to incorporate text reuse evidence when exploring other cases in early modern scholarship. This highlights the adaptability and scalability of text similarity analysis as a valuable tool for advancing literary studies and intellectual history.

Urdu Text Reuse Detection at Phrasal level using Sentence Transformer-based approach

Urdu Text Reuse Detection at Phrasal level using Sentence Transformer-based approach

Impresso Text Reuse at Scale. An interface for the exploration of text reuse data in semantically enriched historical newspapers.

Text Reuse reveals meaningful reiterations of text in large corpora. Humanities researchers use text reuse to study, e.g., the posterior reception of influential texts or to reveal evolving publication practices of historical media. This research is often supported by interactive visualizations which highlight relations and differences between text segments. In this paper, we build on earlier work in this domain. We present impresso Text Reuse at Scale, the to our knowledge first interface which integrates text reuse data with other forms of semantic enrichment to enable a versatile and scalable exploration of intertextual relations in historical newspaper corpora. The Text Reuse at Scale interface was developed as part of the impresso project and combines powerful search and filter operations with close and distant reading perspectives. We integrate text reuse data with enrichments derived from topic modeling, named entity recognition and classification, language and document type detection as well as a rich set of newspaper metadata. We report on historical research objectives and common user tasks for the analysis of historical text reuse data and present the prototype interface together with the results of a user evaluation.

Content Generation in the Age of Mechanical Reproduction

Abstract: This article reconsiders the role of compiling in the modern history of authorship. Nineteenth-century readers viewed compiling as the purest form of "book-making," a mechanistic, market-oriented model of authorship that stood in opposition to authorial genius. The article examines these authorial models' intertwined origins in emergent industrial capitalism, and argues that book-making retained currency as a model into the early twentieth century partly because unattributed text reuse remained common. It also argues that in the aggregate, unattributed text reuse had epistemic and informational effects that anticipated challenges we are grappling with following the development of large language models.

Cross-lingual Text Reuse Detection at Document Level for English-Urdu Language Pair

In recent years, the problem of Cross-Lingual Text Reuse Detection (CLTRD) has gained the interest of the research community due to the availability of large digital repositories and automatic Machine Translation (MT) systems. These systems are readily available and openly accessible, which makes it easier to reuse text across languages but hard to detect. In previous studies, different corpora and methods have been developed for CLTRD at the sentence/passage level for the English-Urdu language pair. However, there is a lack of large standard corpora and methods for CLTRD for the English-Urdu language pair at the document level. To overcome this limitation, the significant contribution of this study is the development of a large benchmark cross-lingual (English-Urdu) text reuse corpus, called the TREU (Text Reuse for English-Urdu) corpus. It contains English to Urdu real cases of text reuse at the document level. The corpus is manually labelled into three categories (Wholly Derived = 672, Partially Derived = 888, and Non Derived = 697) with the source text in English and the derived text in the Urdu language. Another contribution of this study is the evaluation of the TREU corpus using a diversified range of methods to show its usefulness and how it can be utilized in the development of automatic methods for measuring cross-lingual (English-Urdu) text reuse at the document level. The best evaluation results, for both binary ( F 1 = 0.78) and ternary ( F 1 = 0.66) classification tasks, are obtained using a combination of all Translation plus Mono-lingual Analysis (T+MA) based methods. The TREU corpus is publicly available to promote CLTRD research in an under-resourced language, i.e., Urdu.

Detecting translation borrowings in huge text collections using various methods

The purpose of this work is to investigate the problem of detecting transportable borrowings and text reuse. The article proposes a monolingual solution to this problem: translating the suspicious material into language collections for additional monolingual analysis. One of the major requirements for the suggested technique is robustness against machine learning ambiguities. The next step in the document analysis is split into two parts. The authors begin by retrieving documents-candidates that are similarity to other types of text recurrence. The paper proposes retrieving texts utilizing word clusters formed using distributional semantic for robustness. In the second stage, the authors use deep learning neural networks to compare the suspected document to candidates utilizing phrase embedding. The experimentation is carried out for the language pair “English-Arabic” on both articles and synthetic data.

Detecting the influence of the Chinese guiding cases: a text reuse approach

Socialist courts are supposed to apply the law, not make it, and socialist legality denies judicial decisions any precedential status. In 2011, the Chinese Supreme People’s Court designated selected decisions as Guiding Cases to be referred to by all judges when adjudicating similar disputes. One decade on, the paucity of citations to Guiding Cases has been taken as demonstrating the incongruity of case-based adjudication and the socialist legal tradition. Citations are, however, an imperfect measure of influence. Reproduction of language uniquely traceable to Guiding Cases can also be evidence of their impact on judicial decision-making. We employ a local alignment tool to detect unattributed text reuse of Guiding Cases in local court decisions. Our findings suggest that Guiding Cases are more consequential than commonly assumed, thereby complicating prevailing narratives about the antagonism of socialist legality to case law.

Developing an Urdu Lemmatizer Using a Dictionary-Based Lookup Approach

Lemmatization aims at returning the root form of a word. The lemmatizer is envisioned as a vital instrument that can assist in many Natural Language Processing (NLP) tasks. These tasks include Information Retrieval, Word Sense Disambiguation, Machine Translation, Text Reuse, and Plagiarism Detection. Previous studies in the literature have focused on developing lemmatizers using rule-based approaches for English and other highly-resourced languages. However, there have been no thorough efforts for the development of a lemmatizer for most South Asian languages, specifically Urdu. Urdu is a morphologically rich language with many inflectional and derivational forms. This makes the development of an efficient Urdu lemmatizer a challenging task. A standardized lemmatizer would contribute towards establishing much-needed methodological resources for this low-resourced language, which are required to boost the performance of many Urdu NLP applications. This paper presents a lemmatization system for the Urdu language, based on a novel dictionary lookup approach. The contributions made through this research are the following: (1) the development of a large benchmark corpus for the Urdu language, (2) the exploration of the relationship between parts of speech tags and the lemmatizer, and (3) the development of standard approaches for an Urdu lemmatizer. Furthermore, we experimented with the impact of Part of Speech (PoS) on our proposed dictionary lookup approach. The empirical results showed that we achieved the best accuracy score of 76.44% through the proposed dictionary lookup approach.

Reception Reader: Exploring Text Reuse in Early Modern British Publications

The Reception Reader is a web tool for studying text reuse in the Early English Books Online (EEBO-TCP) and Eighteenth Century Collections Online (ECCO) data. Users can: 1) explore a visual overview of the reception of a work, or its incoming connections, across time based on shared text segments, 2) interactively survey the details of connected documents, and 3) examine the context of reused text for "close reading". We show examples of how the tool streamlines research and exploration tasks, and discuss the utility and limitations of the user interface along with its current data sources.

A large dataset of scientific text reuse in Open-Access publications

We present the Webis-STEREO-21 dataset, a massive collection of Scientific Text Reuse in Open-access publications. It contains 91 million cases of reused text passages found in 4.2 million unique open-access publications. Cases range from overlap of as few as eight words to near-duplicate publications and include a variety of reuse types, ranging from boilerplate text to verbatim copying to quotations and paraphrases. Featuring a high coverage of scientific disciplines and varieties of reuse, as well as comprehensive metadata to contextualize each case, our dataset addresses the most salient shortcomings of previous ones on scientific writing. The Webis-STEREO-21 does not indicate if a reuse case is legitimate or not, as its focus is on the general study of text reuse in science, which is legitimate in the vast majority of cases. It allows for tackling a wide range of research questions from different scientific backgrounds, facilitating both qualitative and quantitative analysis of the phenomenon as well as a first-time grounding on the base rate of text reuse in scientific publications.

Textual Migration Across the Baltic Sea

In this paper, we present a database and an interface on text reuse between newspapers and journals published in the Swedish language in Sweden and Finland during the 1645–1918 time frame. Using two national, digital newspaper collections, we detected their textual similarities with a computational method to study the textual migration, i.e., information flows, between the two countries. For purposes of this project, we developed a database of detected clusters of text reuse and an online interface to search, examine and analyse the transnational movement of information. The database, Text Reuse in the Swedish-language Press, 1645–1918, is accessible online and includes texts from over 1,100 newspapers and journals published at approximately 150 locations at various times during the 274-year time frame.