Metaphoric Paraphrase Generation

This work describes the task of metaphoric paraphrase generation, in which we are given a literal sentence and are charged with generating a metaphoric paraphrase. We propose two different models for this task: a lexical replacement baseline and a novel sequence to sequence model, 'metaphor masking', that generates free metaphoric paraphrases. We use crowdsourcing to evaluate our results, as well as developing an automatic metric for evaluating metaphoric paraphrases. We show that while the lexical replacement baseline is capable of producing accurate paraphrases, they often lack metaphoricity, while our metaphor masking model excels in generating metaphoric sentences while performing nearly as well with regard to fluency and paraphrase quality.Comment: 10 pages, 3 figure

Fearsome Worlds and Uncanny Children:Gothic Early Childhoods in Condé’s La migration des coeurs and Kincaid’s The Autobiography of My Mother

Gothic depictions of early childhood and its antecedents from conception to childbirth stand to fundamentally shape readers’ understanding of colonialism across the transnational and translinguistic space of the Caribbean. This effect is particularly visible in contemporary novels such as Maryse Condé’s La Migration des coeurs (1995) and Jamaica Kincaid’s The Autobiography of My Mother (1996), which not only have been interpreted as rewritings of Wuthering Heights but also draw on a larger, more multicultural Gothic literary tradition. In their renderings of sexual violence, doomed pregnancies, and motherless infancy, Condé and Kincaid appropriate and edit Gothic conventions, highlighting persisting ramifications of the colonial project for women and children. Gothic youth also functions as a subversive site of resistance with the potential to dismantle imperialist ideologies and systems

Authenticity and Ephemerality: The Memes of Transcultural Production in Italian Diasporic Culture

This dissertation seeks to contribute a new model for the observation, interpretation, and analysis of Italian and American cultures utilising a semiotic-memetic grammar for analysing and interpreting culture as it transforms and disseminates through time and space. Semioticians, linguists, philosophers, historians, and cultural theorists have written on culture and its relation to language, ethnicity, and identity perception. However, the mechanism for the arrival to specific loci is often overlooked. For the purposes of this study, the cultural systems in question are diasporic Italian manifested in the form of the Italian Americans operating in the periphery (USA) and peninsular/insular Italians operating in the centre (Italy). This dissertation addresses the question of how meaning is constructed, maintained, and propagated in the periphery by diasporic peoples with general inferences on both Italian Diasporic culture in the United States, and specifically a cohort of Americans of Italian, mixed Italian descent that reside in Mahoning Valley in the state of Ohio, USA. I argue that using signs that arrived via memes i.e., non-biologically spread cultural data to the United States through migratory flows, American Italians have the ability to semiotically interpret Italian signs thereby maintaining an authentic and ephemeral connection to Italy while in the periphery. In the present study, signs found in the peripheries of Italy as centre that work in unison to create meaning or Memetic Codes Clusters have been identified and defined as interpretable and communicable cultural value systems. They are examples of multimodal structures operating as memes outside of an origination point connecting and maintaining perception to a core culture: cultures that have historically exerted influence due to hegemony, mass communication, and popular appeal. Multiple examples from a selection of targeted audiovisual and literary texts have been correlated with the aforementioned clusters serving as aesthetic markers. Preliminary findings suggest there are discernible semiotic attributes contained in both samples that illustrate the fecundity and hybridisation of Italian culture in the periphery. Keywords: culture, diaspora, Italian America, memes, semiotic

Artistic communication as an object of semiotics and linguistic aesthetics

The paper addresses the concept of artistic communication as a type of semiotic interaction in the discourses of art. Semiotic methodologies for modelling the sign and the communicative act, developed in the works of Gottlob Frege, Gustav Shpet, Jan Mukařovský, Roman Jakobson, Juri Lotman, Umberto Eco, Suren Zolyan, and some other semioticians, are discussed with a focus on the models of aesthetic sign and the corresponding models of semiosis in relation to artistic systems. The study focuses on the discourses of verbal art in its various manifestations (poetry, prose, drama, performance, spoken word, etc.) as material for a linguistic analysis of artistic communication. The paper specifically discusses the linguistic representations of artistic discourse within a model of aesthetic semiosis. The resulting model of artistic communication in verbal art is presented as a synthesis of Jakobson’s scheme of communicative act and its important specification in Lotman’s model of “literary communication”. Based on the existing models of sign, semiosis, and communication (taking Jakobson’s scheme as the main framework), a synthetic, linguo-aesthetic model of artistic communication is outlined, considering together the linguistic, semiotic, and aesthetic parameters of the artistic act

Altered Anatomies

The dawning possibility of changing our physical forms through greater and greater levels of technological intervention confronts us with ancient philosophical questions, not just of who one is, but also of who one wants to be. These questions exist as overt interrogations and non-verbal desires. One avenue for the exploration of these desires has been the creation and manipulation of bodies beyond the human : altered anatomies. Such transhumans have been with us since ancient times and continue to proliferate today. This thesis examines the work of the artist Bobby Campbell to explore those bodies and desires. The thesis begins with a brief look at the impulse to change one’s form. This is followed by a discussion of particular contexts relevant to the artist’s work. The major thesis work, a large-scale, multi-part painting of altered anatomies, is then critically examined. Finally, the epilogue reveals some of the inner monologue of the artist in undertaking such work.Master of Fine Arts (MFA)Art and DesignUniversity of Michiganhttp://deepblue.lib.umich.edu/bitstream/2027.42/41244/3/Campbell.pd

Attention-based Approaches for Text Analytics in Social Media and Automatic Summarization

[ES] Hoy en día, la sociedad tiene acceso y posibilidad de contribuir a grandes cantidades de contenidos presentes en Internet, como redes sociales, periódicos online, foros, blogs o plataformas de contenido multimedia. Todo este tipo de medios han tenido, durante los últimos años, un impacto abrumador en el día a día de individuos y organizaciones, siendo actualmente medios predominantes para compartir, debatir y analizar contenidos online. Por este motivo, resulta de interés trabajar sobre este tipo de plataformas, desde diferentes puntos de vista, bajo el paraguas del Procesamiento del Lenguaje Natural. En esta tesis nos centramos en dos áreas amplias dentro de este campo, aplicadas al análisis de contenido en línea: análisis de texto en redes sociales y resumen automático. En paralelo, las redes neuronales también son un tema central de esta tesis, donde toda la experimentación se ha realizado utilizando enfoques de aprendizaje profundo, principalmente basados en mecanismos de atención. Además, trabajamos mayoritariamente con el idioma español, por ser un idioma poco explorado y de gran interés para los proyectos de investigación en los que participamos. Por un lado, para el análisis de texto en redes sociales, nos enfocamos en tareas de análisis afectivo, incluyendo análisis de sentimientos y detección de emociones, junto con el análisis de la ironía. En este sentido, se presenta un enfoque basado en Transformer Encoders, que consiste en contextualizar \textit{word embeddings} pre-entrenados con tweets en español, para abordar tareas de análisis de sentimiento y detección de ironía. También proponemos el uso de métricas de evaluación como funciones de pérdida, con el fin de entrenar redes neuronales, para reducir el impacto del desequilibrio de clases en tareas \textit{multi-class} y \textit{multi-label} de detección de emociones. Adicionalmente, se presenta una especialización de BERT tanto para el idioma español como para el dominio de Twitter, que tiene en cuenta la coherencia entre tweets en conversaciones de Twitter. El desempeño de todos estos enfoques ha sido probado con diferentes corpus, a partir de varios \textit{benchmarks} de referencia, mostrando resultados muy competitivos en todas las tareas abordadas. Por otro lado, nos centramos en el resumen extractivo de artículos periodísticos y de programas televisivos de debate. Con respecto al resumen de artículos, se presenta un marco teórico para el resumen extractivo, basado en redes jerárquicas siamesas con mecanismos de atención. También presentamos dos instancias de este marco: \textit{Siamese Hierarchical Attention Networks} y \textit{Siamese Hierarchical Transformer Encoders}. Estos sistemas han sido evaluados en los corpora CNN/DailyMail y NewsRoom, obteniendo resultados competitivos en comparación con otros enfoques extractivos coetáneos. Con respecto a los programas de debate, se ha propuesto una tarea que consiste en resumir las intervenciones transcritas de los ponentes, sobre un tema determinado, en el programa "La Noche en 24 Horas". Además, se propone un corpus de artículos periodísticos, recogidos de varios periódicos españoles en línea, con el fin de estudiar la transferibilidad de los enfoques propuestos, entre artículos e intervenciones de los participantes en los debates. Este enfoque muestra mejores resultados que otras técnicas extractivas, junto con una transferibilidad de dominio muy prometedora.[CA] Avui en dia, la societat té accés i possibilitat de contribuir a grans quantitats de continguts presents a Internet, com xarxes socials, diaris online, fòrums, blocs o plataformes de contingut multimèdia. Tot aquest tipus de mitjans han tingut, durant els darrers anys, un impacte aclaparador en el dia a dia d'individus i organitzacions, sent actualment mitjans predominants per compartir, debatre i analitzar continguts en línia. Per aquest motiu, resulta d'interès treballar sobre aquest tipus de plataformes, des de diferents punts de vista, sota el paraigua de l'Processament de el Llenguatge Natural. En aquesta tesi ens centrem en dues àrees àmplies dins d'aquest camp, aplicades a l'anàlisi de contingut en línia: anàlisi de text en xarxes socials i resum automàtic. En paral·lel, les xarxes neuronals també són un tema central d'aquesta tesi, on tota l'experimentació s'ha realitzat utilitzant enfocaments d'aprenentatge profund, principalment basats en mecanismes d'atenció. A més, treballem majoritàriament amb l'idioma espanyol, per ser un idioma poc explorat i de gran interès per als projectes de recerca en els que participem. D'una banda, per a l'anàlisi de text en xarxes socials, ens enfoquem en tasques d'anàlisi afectiu, incloent anàlisi de sentiments i detecció d'emocions, juntament amb l'anàlisi de la ironia. En aquest sentit, es presenta una aproximació basada en Transformer Encoders, que consisteix en contextualitzar \textit{word embeddings} pre-entrenats amb tweets en espanyol, per abordar tasques d'anàlisi de sentiment i detecció d'ironia. També proposem l'ús de mètriques d'avaluació com a funcions de pèrdua, per tal d'entrenar xarxes neuronals, per reduir l'impacte de l'desequilibri de classes en tasques \textit{multi-class} i \textit{multi-label} de detecció d'emocions. Addicionalment, es presenta una especialització de BERT tant per l'idioma espanyol com per al domini de Twitter, que té en compte la coherència entre tweets en converses de Twitter. El comportament de tots aquests enfocaments s'ha provat amb diferents corpus, a partir de diversos \textit{benchmarks} de referència, mostrant resultats molt competitius en totes les tasques abordades. D'altra banda, ens centrem en el resum extractiu d'articles periodístics i de programes televisius de debat. Pel que fa a l'resum d'articles, es presenta un marc teòric per al resum extractiu, basat en xarxes jeràrquiques siameses amb mecanismes d'atenció. També presentem dues instàncies d'aquest marc: \textit{Siamese Hierarchical Attention Networks} i \textit{Siamese Hierarchical Transformer Encoders}. Aquests sistemes s'han avaluat en els corpora CNN/DailyMail i Newsroom, obtenint resultats competitius en comparació amb altres enfocaments extractius coetanis. Pel que fa als programes de debat, s'ha proposat una tasca que consisteix a resumir les intervencions transcrites dels ponents, sobre un tema determinat, al programa "La Noche en 24 Horas". A més, es proposa un corpus d'articles periodístics, recollits de diversos diaris espanyols en línia, per tal d'estudiar la transferibilitat dels enfocaments proposats, entre articles i intervencions dels participants en els debats. Aquesta aproximació mostra millors resultats que altres tècniques extractives, juntament amb una transferibilitat de domini molt prometedora.[EN] Nowadays, society has access, and the possibility to contribute, to large amounts of the content present on the internet, such as social networks, online newspapers, forums, blogs, or multimedia content platforms. These platforms have had, during the last years, an overwhelming impact on the daily life of individuals and organizations, becoming the predominant ways for sharing, discussing, and analyzing online content. Therefore, it is very interesting to work with these platforms, from different points of view, under the umbrella of Natural Language Processing. In this thesis, we focus on two broad areas inside this field, applied to analyze online content: text analytics in social media and automatic summarization. Neural networks are also a central topic in this thesis, where all the experimentation has been performed by using deep learning approaches, mainly based on attention mechanisms. Besides, we mostly work with the Spanish language, due to it is an interesting and underexplored language with a great interest in the research projects we participated in. On the one hand, for text analytics in social media, we focused on affective analysis tasks, including sentiment analysis and emotion detection, along with the analysis of the irony. In this regard, an approach based on Transformer Encoders, based on contextualizing pretrained Spanish word embeddings from Twitter, to address sentiment analysis and irony detection tasks, is presented. We also propose the use of evaluation metrics as loss functions, in order to train neural networks for reducing the impact of the class imbalance in multi-class and multi-label emotion detection tasks. Additionally, a specialization of BERT both for the Spanish language and the Twitter domain, that takes into account inter-sentence coherence in Twitter conversation flows, is presented. The performance of all these approaches has been tested with different corpora, from several reference evaluation benchmarks, showing very competitive results in all the tasks addressed. On the other hand, we focused on extractive summarization of news articles and TV talk shows. Regarding the summarization of news articles, a theoretical framework for extractive summarization, based on siamese hierarchical networks with attention mechanisms, is presented. Also, we present two instantiations of this framework: Siamese Hierarchical Attention Networks and Siamese Hierarchical Transformer Encoders. These systems were evaluated on the CNN/DailyMail and the NewsRoom corpora, obtaining competitive results in comparison to other contemporary extractive approaches. Concerning the TV talk shows, we proposed a text summarization task, for summarizing the transcribed interventions of the speakers, about a given topic, in the Spanish TV talk shows of the ``La Noche en 24 Horas" program. In addition, a corpus of news articles, collected from several Spanish online newspapers, is proposed, in order to study the domain transferability of siamese hierarchical approaches, between news articles and interventions of debate participants. This approach shows better results than other extractive techniques, along with a very promising domain transferability.González Barba, JÁ. (2021). Attention-based Approaches for Text Analytics in Social Media and Automatic Summarization [Tesis doctoral]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/172245TESI

Can humain association norm evaluate latent semantic analysis?

This paper presents the comparison of word association norm created by a psycholinguistic experiment to association lists generated by algorithms operating on text corpora. We compare lists generated by Church and Hanks algorithm and lists generated by LSA algorithm. An argument is presented on how those automatically generated lists reflect real semantic relations