Drawing Elena Ferrante's Profile. Workshop Proceedings, Padova, 7 September 2017

Elena Ferrante is an internationally acclaimed Italian novelist whose real identity has been kept secret by E/O publishing house for more than 25 years. Owing to her popularity, major Italian and foreign newspapers have long tried to discover her real identity. However, only a few attempts have been made to foster a scientific debate on her work. In 2016, Arjuna Tuzzi and Michele Cortelazzo led an Italian research team that conducted a preliminary study and collected a well-founded, large corpus of Italian novels comprising 150 works published in the last 30 years by 40 different authors. Moreover, they shared their data with a select group of international experts on authorship attribution, profiling, and analysis of textual data: Maciej Eder and Jan Rybicki (Poland), Patrick Juola (United States), Vittorio Loreto and his research team, Margherita Lalli and Francesca Tria (Italy), George Mikros (Greece), Pierre Ratinaud (France), and Jacques Savoy (Switzerland). The chapters of this volume report the results of this endeavour that were first presented during the international workshop Drawing Elena Ferrante's Profile in Padua on 7 September 2017 as part of the 3rd IQLA-GIAT Summer School in Quantitative Analysis of Textual Data. The fascinating research findings suggest that Elena Ferrante\u2019s work definitely deserves \u201cmany hands\u201d as well as an extensive effort to understand her distinct writing style and the reasons for her worldwide success

Stylometry in a bilingual setup

The method of stylometry by most frequent words does not allow direct comparison of original texts and their translations, i.e. across languages. For instance, in a bilingual Czech-German text collection containing parallel texts (originals and translations in both directions, along with Czech and German translations from other languages), authors would not cluster across languages, since frequency word lists for any Czech texts are obviously going to be more similar to each other than to a German text, and the other way round. We have tried to come up with an interlingua that would remove the language-specific features and possibly keep the linguistically independent features of individual author signal, if they exist. We have tagged, lemmatized, and parsed each language counterpart with the corresponding language model in UDPipe, which provides a linguistic markup that is cross-lingual to a significant extent. We stripped the output of language-dependent items, but that alone did not help much. As a next step, we transformed the lemmas of both language counterparts into shared pseudolemmas based on a very crude Czech-German glossary, with a 95.6% success. We show that, for stylometric methods based on the most frequent words, we can do without translations

Stylistic Fingerprints, POS-tags and Inflected Languages: A Case Study in Polish

In stylometric investigations, frequencies of the most frequent words (MFWs) and character n-grams outperform other style-markers, even if their performance varies significantly across languages. In inflected languages, word endings play a prominent role, and hence different word forms cannot be recognized using generic text tokenization. Countless inflected word forms make frequencies sparse, making most statistical procedures complicated. Presumably, applying one of the NLP techniques, such as lemmatization and/or parsing, might increase the performance of classification. The aim of this paper is to examine the usefulness of grammatical features (as assessed via POS-tag n-grams) and lemmatized forms in recognizing authorial profiles, in order to address the underlying issue of the degree of freedom of choice within lexis and grammar. Using a corpus of Polish novels, we performed a series of supervised authorship attribution benchmarks, in order to compare the classification accuracy for different types of lexical and syntactic style-markers. Even if the performance of POS-tags as well as lemmatized forms was notoriously worse than that of lexical markers, the difference was not substantial and never exceeded ca. 15%

The stylometry of film dialogue : pros and pitfalls

We examine film dialogue with quantitative textual analysis (stylometry, sentiment analysis, distant reading). Working with transcribed dialogue in almost 300 productions, we explore the complex way in which most-frequent-words-based stylometry and lexicon-based sentiment analysis produce patterns of similarity and difference between screenwriters and/or a priori IMDB-defined genres. In fact, some of our results show that counting and comparing very frequent word lists reveals further similarities: of theme, implied audience, stylistic patternings. The results are encouraging enough to suggest that such quantitative approach to film dialogue may become a welcome addition to the arsenal of film studies methodology

StyloMetrix: An Open-Source Multilingual Tool for Representing Stylometric Vectors

This work aims to provide an overview on the open-source multilanguage tool called StyloMetrix. It offers stylometric text representations that cover various aspects of grammar, syntax and lexicon. StyloMetrix covers four languages: Polish as the primary language, English, Ukrainian and Russian. The normalized output of each feature can become a fruitful course for machine learning models and a valuable addition to the embeddings layer for any deep learning algorithm. We strive to provide a concise, but exhaustive overview on the application of the StyloMetrix vectors as well as explain the sets of the developed linguistic features. The experiments have shown promising results in supervised content classification with simple algorithms as Random Forest Classifier, Voting Classifier, Logistic Regression and others. The deep learning assessments have unveiled the usefulness of the StyloMetrix vectors at enhancing an embedding layer extracted from Transformer architectures. The StyloMetrix has proven itself to be a formidable source for the machine learning and deep learning algorithms to execute different classification tasks.Comment: 26 pages, 6 figures, pre-print for the conferenc

Challenging stylometry: The authorship of the baroque play La Segunda Celestina

The aim of this study was to verify the possibility of Sor Juana Ine´ s de la Cruz authoring the anonymous part of the baroque play La Segunda Celestina, commissioned to Agustın de Salazar, and left unfinished after his death. This is a first systematic stylometric study on this problem and a baroque hispanoamerican text. In our study, we faced building a balanced corpus from few available resources, and took extensive evaluation measures to deal with unclear stylometric signals. We use a variety of established attribution and verification methods, and introduce a novel evaluation procedure of examining historic texts with scarce corpora. The results support Sor Juana’s authorship, and unravel new connections between her and other authors of the time, showing, still undermined, powerful impact of her works on the epoch. The solutions adopted in solving methodological problems of such a complex task show how stylometry can overcome similar challenges

An open stylometric system based on multilevel text analysis

An open stylometric system based on multilevel text analysis Stylometric techniques are usually applied to a limited number of typical tasks, such as authorship attribution, genre analysis, or gender studies. However, they could be applied to several tasks beyond this canonical set, if only stylometric tools were more accessible to users from different areas of the humanities and social sciences. This paper presents a general idea, followed by a fully functional prototype of an open stylometric system that facilitates its wide use through to two aspects: technical and research flexibility. The system relies on a server installation combined with a web-based user interface. This frees the user from the necessity of installing any additional software. At the same time, the system offers a variety of ways in which the input texts can be analysed: they include not only the usual lexical level, but also deep-level linguistic features. This enables a range of possible applications, from typical stylometric tasks to the semantic analysis of text documents. The internal architecture of the system relies on several well-known software packages: a collection of language tools (for text pre-processing), Stylo (for stylometric analysis) and Cluto (for text clustering). The paper presents: (1) The idea behind the system from the user’s perspective. (2) The architecture of the system, with a focus on data processing. (3) Features for text description. (4) The use of analytical systems such as Stylo and Cluto. The presentation is illustrated with example applications.   Otwarty system stylometryczny wykorzystujący wielopoziomową analizę języka  Zastosowania metod stylometrycznych na ogół ograniczają się do kilku typowych problemów badawczych, takich jak atrybucja autorska, styl gatunków literackich czy studia nad zróżnicowaniem stylistycznym kobiet i mężczyzn. Z pewnością dałoby się je z powodzeniem zastosować również do wielu innych problemów klasyfikacji tekstów, gdyby tylko owe metody oraz odpowiednie narzędzia były bardziej dostępne dla uczonych reprezentujących różne dyscypliny nauk humanistycznych i społecznych. Artykuł niniejszy omawia założenia teoretyczne oraz w pełni funkcjonalny prototyp otwartego systemu stylometrycznego, którego szerokie zastosowanie umożliwią dwie jego cechy: elastyczność techniczna oraz dostosowywalność do różnych pytań badawczych. System opiera się na instalacji serwerowej sprzęgniętej z sieciowym interfejsem użytkownika. Uwalnia to użytkownika od konieczności instalowania jakichkolwiek dodatkowych programów. Jednocześnie system oferuje wiele sposobów analizowania tekstów nie tylko na poziomie leksykalnym, lecz także poprzez cechy językowe niskiego poziomu. Daje to możliwość stosowania systemu na wiele różnych sposobów, od typowych testów stylometrycznych do analizy semantycznej dokumentów. Wewnętrzna architektura systemu składa się z wielu elementów znanych ze swej funkcjonalności, w tym z pakietu Stylo przeznaczonego do analiz stylometrycznych oraz pakietu Cluto służącego do zaawansowanej analizy skupień. Artykuł omawia: (1) Koncepcję całego systemu, postrzeganą z punktu widzenia użytkownika, (2) Architekturę systemu oraz jego elementy odpowiedzialne za przetwarzanie tekstu, (3) Cechy językowe służące do opisu dokumentów, (4) Zastosowanie modułów analizy danych, takich jak Stylo czy Cluto. W artykule zostały też przedstawione przykładowe zastosowania systemu

An open stylometric system based on multilevel text analysis

An open stylometric system based on multilevel text analysisStylometric techniques are usually applied to a limited number of typical tasks, such as authorship attribution, genre analysis, or gender studies. However, they could be applied to several tasks beyond this canonical set, if only stylometric tools were more accessible to users from different areas of the humanities and social sciences. This paper presents a general idea, followed by a fully functional prototype of an open stylometric system that facilitates its wide use through to two aspects: technical and research flexibility. The system relies on a server installation combined with a web-based user interface. This frees the user from the necessity of installing any additional software. At the same time, the system offers a variety of ways in which the input texts can be analysed: they include not only the usual lexical level, but also deep-level linguistic features. This enables a range of possible applications, from typical stylometric tasks to the semantic analysis of text documents. The internal architecture of the system relies on several well-known software packages: a collection of language tools (for text pre-processing), Stylo (for stylometric analysis) and Cluto (for text clustering). The paper presents: (1) The idea behind the system from the user’s perspective. (2) The architecture of the system, with a focus on data processing. (3) Features for text description. (4) The use of analytical systems such as Stylo and Cluto. The presentation is illustrated with example applications. Otwarty system stylometryczny wykorzystujący wielopoziomową analizę języka Zastosowania metod stylometrycznych na ogół ograniczają się do kilku typowych problemów badawczych, takich jak atrybucja autorska, styl gatunków literackich czy studia nad zróżnicowaniem stylistycznym kobiet i mężczyzn. Z pewnością dałoby się je z powodzeniem zastosować również do wielu innych problemów klasyfikacji tekstów, gdyby tylko owe metody oraz odpowiednie narzędzia były bardziej dostępne dla uczonych reprezentujących różne dyscypliny nauk humanistycznych i społecznych. Artykuł niniejszy omawia założenia teoretyczne oraz w pełni funkcjonalny prototyp otwartego systemu stylometrycznego, którego szerokie zastosowanie umożliwią dwie jego cechy: elastyczność techniczna oraz dostosowywalność do różnych pytań badawczych. System opiera się na instalacji serwerowej sprzęgniętej z sieciowym interfejsem użytkownika. Uwalnia to użytkownika od konieczności instalowania jakichkolwiek dodatkowych programów. Jednocześnie system oferuje wiele sposobów analizowania tekstów nie tylko na poziomie leksykalnym, lecz także poprzez cechy językowe niskiego poziomu. Daje to możliwość stosowania systemu na wiele różnych sposobów, od typowych testów stylometrycznych do analizy semantycznej dokumentów. Wewnętrzna architektura systemu składa się z wielu elementów znanych ze swej funkcjonalności, w tym z pakietu Stylo przeznaczonego do analiz stylometrycznych oraz pakietu Cluto służącego do zaawansowanej analizy skupień. Artykuł omawia: (1) Koncepcję całego systemu, postrzeganą z punktu widzenia użytkownika, (2) Architekturę systemu oraz jego elementy odpowiedzialne za przetwarzanie tekstu, (3) Cechy językowe służące do opisu dokumentów, (4) Zastosowanie modułów analizy danych, takich jak Stylo czy Cluto. W artykule zostały też przedstawione przykładowe zastosowania systemu

Going Deeper than Supervised Discretisation in Processing of Stylometric Features

Rough set theory is employed in cases where data are incomplete and inconsistent and an ap- proximation of concepts is needed. The classical approach works for discrete data and allows only nominal classification. To induce the best rules, access to all available information is ad- vantageous, which can be endangered if discretisation is a necessary step in the data preparation stage. Discretisation, even executed with taking into account class labels of instances, brings some information loss. The research methodology illustrated in this paper is dedicated to ex- tended transformations of continuous input features into categorical, with the goal of enhancing the performance of rule-based classifiers, constructed with rough set data mining. The experi- ments were carried out in the stylometry domain, with its key task of authorship attribution. The obtained results indicate that supporting supervised discretisation with elements of unsuper- vised transformations can lead to enhanced predictions, which shows the merits of the proposed research framework