Brief of Digital Humanities And Law Scholars as Amici Curiae In Support Of Defendant-Appellees And Affirmance, (The Authors Guild, Inc., et al., v. Google, Inc., et al.)

Amici are over 150 professors and scholars who teach, write, and research in computer science, the digital humanities, linguistics or law, and two associations that represent Digital Humanities scholars generally.2 Amici have an interest in this case because of its potential impact on their ability to discover and understand, through automated means, the data in and relationships among textual works. Legal Scholar Amici also have an interest in the sound development of intellectual property law. Resolution of the legal issue of copying for non-expressive uses has far-reaching implications for the scope of copyright protection, a subject germane to Amici’s professional interests and one about which they have great expertise. Amici speak only to the issue of copying for non-expressive uses. A complete list of individual Amici is attached as Appendix A. Mass digitization is a key enabler of socially valuable computational and statistical research (often called “data mining” or “text mining”). While the practice of data mining has been used for several decades in traditional scientific disciplines such as astrophysics and in social sciences such as economics, it has only recently become technologically and economically feasible within the humanities. This has led to a revolution, dubbed “Digital Humanities,” ranging across subjects such as literature and linguistics to history and philosophy. New scholarly endeavors enabled by Digital Humanities advancements are still in their infancy but have enormous potential to contribute to our collective understanding of the cultural, political, and economic relationships among various collections (or corpora) of works—including copyrighted works—and with society. The Court’s ruling in this case on the legality of mass digitization could dramatically affect the future of work in the Digital Humanities

Brief of Digital Humanities And Law Scholars as Amici Curiae In Support Of Defendant-Appellees And Affirmance, (The Authors Guild, Inc., et al., v. Google, Inc., et al.)

Amici are over 150 professors and scholars who teach, write, and research in computer science, the digital humanities, linguistics or law, and two associations that represent Digital Humanities scholars generally.2 Amici have an interest in this case because of its potential impact on their ability to discover and understand, through automated means, the data in and relationships among textual works. Legal Scholar Amici also have an interest in the sound development of intellectual property law. Resolution of the legal issue of copying for non-expressive uses has far-reaching implications for the scope of copyright protection, a subject germane to Amici’s professional interests and one about which they have great expertise. Amici speak only to the issue of copying for non-expressive uses. A complete list of individual Amici is attached as Appendix A. Mass digitization is a key enabler of socially valuable computational and statistical research (often called “data mining” or “text mining”). While the practice of data mining has been used for several decades in traditional scientific disciplines such as astrophysics and in social sciences such as economics, it has only recently become technologically and economically feasible within the humanities. This has led to a revolution, dubbed “Digital Humanities,” ranging across subjects such as literature and linguistics to history and philosophy. New scholarly endeavors enabled by Digital Humanities advancements are still in their infancy but have enormous potential to contribute to our collective understanding of the cultural, political, and economic relationships among various collections (or corpora) of works—including copyrighted works—and with society. The Court’s ruling in this case on the legality of mass digitization could dramatically affect the future of work in the Digital Humanities

Metaadat

A Macroanalysis: Digital Methods and Literary History című könyv 5. fejezete azt kísérli meg bebizonyítani, hogy a bibliográfiai és demografikus metaadatok számítógépes módszerekkel történő elemzése lehetővé teszi irodalomtörténeti narratívák újraértékelését vagy átírását. A fejezet bemutatja, hogy irodalomtörténeti korszakok és trendek gondolatébresztő perspektívákba helyezhetők a könyvszintű metaadatok – könyvcímek, szerző származása, publikáció dátuma, kitalált helyszín és időpont stb. – makroelemzésével. Az ír-amerikai irodalomhoz kötődő metaadat-adatbázis hasznosításával a szerző újraértékeli az eddig elfogadott ír-amerikai irodalomtörténeti narratívát és egy alternatív perspektívába állítja Charles Fanning elméletét az ír-amerikai írók „elveszett generációjáról.” A metaadatok kontextust teremtenek Fanning irodalomtörténeti olvasatához, és azt sugallják, hogy az ír-amerikai irodalom történetére vonatkozó tudományos feltételezések a szerzők egy homogén csoportjának kisszámú művének elemzésén alapulnak. Absztraktabban fogalmazva a fejezet amellett érvel, hogy a hagyományos irodalomtudósok tévesen gondolják, hogy a nagy merítésen alapuló elemzések helyettesíteni szeretnék a szoros olvasást. Éppen ellenkezőleg, a metaadatok makroelemzése kizárólag a szükséges kontextust teremti meg a szoros olvasáshoz, és új kérdések felvetéséhez, az irodalomtörténet új perspektíváinak megalkotásához járul hozzá

The Science of Sungrazers, Sunskirters, and Other Near-Sun Comets

This review addresses our current understanding of comets that venture close to the Sun, and are hence exposed to much more extreme conditions than comets that are typically studied from Earth. The extreme solar heating and plasma environments that these objects encounter change many aspects of their behaviour, thus yielding valuable information on both the comets themselves that complements other data we have on primitive solar system bodies, as well as on the near-solar environment which they traverse. We propose clear definitions for these comets: We use the term near-Sun comets to encompass all objects that pass sunward of the perihelion distance of planet Mercury (0.307 AU). Sunskirters are defined as objects that pass within 33 solar radii of the Sun’s centre, equal to half of Mercury’s perihelion distance, and the commonly-used phrase sungrazers to be objects that reach perihelion within 3.45 solar radii, i.e. the fluid Roche limit. Finally, comets with orbits that intersect the solar photosphere are termed sundivers. We summarize past studies of these objects, as well as the instruments and facilities used to study them, including space-based platforms that have led to a recent revolution in the quantity and quality of relevant observations. Relevant comet populations are described, including the Kreutz, Marsden, Kracht, and Meyer groups, near-Sun asteroids, and a brief discussion of their origins. The importance of light curves and the clues they provide on cometary composition are emphasized, together with what information has been gleaned about nucleus parameters, including the sizes and masses of objects and their families, and their tensile strengths. The physical processes occurring at these objects are considered in some detail, including the disruption of nuclei, sublimation, and ionisation, and we consider the mass, momentum, and energy loss of comets in the corona and those that venture to lower altitudes. The different components of comae and tails are described, including dust, neutral and ionised gases, their chemical reactions, and their contributions to the near-Sun environment. Comet-solar wind interactions are discussed, including the use of comets as probes of solar wind and coronal conditions in their vicinities. We address the relevance of work on comets near the Sun to similar objects orbiting other stars, and conclude with a discussion of future directions for the field and the planned ground- and space-based facilities that will allow us to address those science topics

A Matter of Scale

Transcript of a staged debate between Julia Flanders and Matthew L. Jockers on the question of how scale is impacting research in the digital humanities. The debate took place on March 18, 2013 at Northeastern University as part of the Boston Area Days of Digital Humanities Conference

Significant Themes in 19th-Century Literature

External factors such as author gender, author nationality, and date of publication affect both the choice of literary themes in novels and the expression of those themes, but the extent of this association is difficult to quantify. In this work, we apply statistical methods to identify and extract hundreds of topics from a corpus of 3,346 works of 19th-century British, Irish, and American fiction. We use these topics as a measurable, data-driven proxy for literary themes. External factors may predict fluctuations in the use of themes and the individual word choices within themes. We use topics to measure the evidence for these associations and whether that evidence is statistically significant

Text analysis with R for students of literature

Text Analysis with R for Students of Literature is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological tool kit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that we simply cannot gather using traditional qualitative methods of close reading and human synthesis. Text Analysis with R for Students of Literature provides a practical introduction to computational text analysis using the open source programming language R. R is extremely popular throughout the sciences and because of its accessibility, R is now used increasingly in other research areas. Readers begin working with text right away and each chapter works through a new technique or process such that readers gain a broad exposure to core R procedures and a basic understanding of the possibilities of computational text analysis at both the micro and macro scale. Each chapter builds on the previous as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each chapter concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book’s focus is on making the technical palatable and making the technical useful and immediately gratifying

Text analysis with R: for students of literature

Now in its second edition, Text Analysis with R provides a practical introduction to computational text analysis using the open source programming language R. R is an extremely popular programming language, used throughout the sciences; due to its accessibility, R is now used increasingly in other research areas. In this volume, readers immediately begin working with text, and each chapter examines a new technique or process, allowing readers to obtain a broad exposure to core R procedures and a fundamental understanding of the possibilities of computational text analysis at both the micro and the macro scale. Each chapter builds on its predecessor as readers move from small scale “microanalysis” of single texts to large scale “macroanalysis” of text corpora, and each concludes with a set of practice exercises that reinforce and expand upon the chapter lessons. The book’s focus is on making the technical palatable and making the technical useful and immediately gratifying. Text Analysis with R is written with students and scholars of literature in mind but will be applicable to other humanists and social scientists wishing to extend their methodological toolkit to include quantitative and computational approaches to the study of text. Computation provides access to information in text that readers simply cannot gather using traditional qualitative methods of close reading and human synthesis. This new edition features two new chapters: one that introduces dplyr and tidyr in the context of parsing and analyzing dramatic texts to extract speaker and receiver data, and one on sentiment analysis using the syuzhet package. It is also filled with updated material in every chapter to integrate new developments in the field, current practices in R style, and the use of more efficient algorithms