Beyond description. Comment on "Approaching human language with complex networks" by Cong & Liu

Comment on "Approaching human language with complex networks" by Cong & Li

Does Scale-Free Syntactic Network Emerge in Second Language Learning?

Language is a complex system during whose operation many properties may emerge spontaneously. Using complex network approach, existing studies have found that, in first language (L1) acquisition, syntactic complex network featuring the scale-free and the small-world properties, will emerge at the age of 24 months. For foreign language (L2) learning, however, researchers have not reached a consensus on whether syntactic network with these two properties will emerge. Therefore, this study adopts complex network approach in L2 learning study, attempting to answer this question. In this study, nine networks are constructed on the basis of English compositions by Chinese students. Properties of these networks reveal that the syntactic network featuring these two properties, instead of emerging suddenly at a certain point, has existed at the very beginning of the L2 learning of Chinese students, and persists throughout the entire process of L2 learning, which is different from what has been found in L1 acquisition. The reason is probably that the already established L1 syntactic system provides foundation for L2 syntactic learning, and L2 learners tend to use the entrenched L1 syntactic network to generate L2 syntactic structures. L2 syntactic learning thus is not characterized by a sudden emergence of syntactic system, but a gradual approximation to the target language, with its own unique properties. For the first time, this study provides a tentative answer to L2 syntactic emergence from the perspective of complex network, and provides a macroscopic description of L2 syntactic developmental trajectory

Language networks: An insight into the language faculty?

Treballs Finals del Màster en Ciència Cognitiva i Llenguatge, Facultat de Filosofia, Universitat de Barcelona, Curs: 2015-2016, Tutor: Antoni Badia CardúsIn this Master’s thesis we will approach language networks with a critical eye from a linguist’s perspective. Are language networks successful in representing key aspects of language? Are the cognitive inferences made from them sound? However, before diving into the particulars of language network research, the reader will need to bear with a somewhat hard to tread introduction (sections 2 and 3) where very basic foundations of network science are laid. In section 4 we will give a critical overview of research into semantic and syntactic networks (focusing on the latter), and in section 5 we will generate and analyze syntactic networks from English and Spanish corpora, and compare our results to those reviewed. We will end in section 6 with a reflection on modelling syntactic networks

Participation of children in the Vietnam War, 1955-1975

This thesis argues that child soldiering is a socially embedded phenomenon. To this end, I analysed child soldiering in the context of the Vietnam War, interviewing former child soldiers about their lives prior, during, and after joining the Viet Cong guerrillas. Deploying an interpretative framework drawing on Bourdieu’s relational sociology, I found that in Vietnam, children’s social context - in particular, the prevalence of Confucianism and communism - consistently guided children's motivations and shaped their experience. The findings of this thesis demonstrate that while ideology and sociocultural practices formed the experience of Vietnamese child soldiers, they were able to negotiate and navigate them in ways that demonstrate considerable agency. The findings of this thesis have the following implications. Firstly, this thesis challenges the 'victim perpetrator' binary, through which child soldiers are often represented. Rather, it underlines that children have agency as deeply social and political actors, who shape and are shaped by their environment. In doing so, this thesis contributes to our understanding of not only child soldiers’ experiences, but also of children in militarised contexts, and specifically the role that everyday social practices play in militarisation of childhood. Secondly, these findings contribute to the literature on the Vietnam War, uncovering new evidence of the many roles that children played in the Viet Cong. The insight that the broader social environment impacted child soldiering in Vietnam can be deployed in future research on child soldiering in under-studied geographical and cultural contexts. Such an understanding will enhance our general knowledge of the phenomenon of child soldiering and the variety of ways in which children participate in war. In doing so, this thesis contributes to broader re-imagining childhood as a complex, nuanced, and dynamic phenomenon

Chinese DE constructions in secondary predication: Historical and typological perspectives

This dissertation investigates the history of Chinese DE [tə] constructions in light of the typology of secondary predication. A secondary predicate, such as hot in He drank the tea hot, is a predicate that provides subsidiary information to a substructure (the participant tea) of the more salient primary event (drank). Mandarin DE features in two strategies: (i) a DE-marked primary event elaborated by a predicate following it, and (ii) a DE-marked secondary predicate preposed to the primary predicate. Focusing on Late Medieval Chinese (7th to mid-13th c.), the study examines the evolution of the DE-marked strategies from three distinctive constructions: resultative [V DE1 VP] by DE1 (得), nominal modification by DE2 (底/的), and secondary predication by DE3 (地). The first theme concerns the interactions between DE2-marked nominalization and DE3-marked secondary predicate constructions. Results show that DE2 and DE3 developed from opposite poles of the attribution vs. predication continuum, overlapping in categories intermediate between prototypical restrictive modification and secondary predication. Their distinctive information-packaging functions are consistently mapped to different construals of a property’s time-stability, which are reflected in their collocational preferences. The second theme of the study deals with the merger of DE1 and DE2 constructions and the creation of the [V DE Pred] topic-comment schema, where [V DE] represents an event as the topic, and Pred makes an assertion about a substructure of V. The discussion focuses on the structural and semantic changes of the [V DE1 VP] construction that facilitate its alignment with the DE2-marked topic-comment construction. The development of DE constructions mirrors semantic shifts between temporally anterior vs. simultaneous relations and conceptual fluidity between event- vs. participant-orientation, parameters that feature in the encoding of secondary predication crosslinguistically (Verkerk 2009, Himmelmann and Schultze-Berndt 2005, van der Auwera and Malchukov 2005, Loeb-Diehl 2005). The findings also suggest a reevaluation of the typology. Notably, semantic orientation is not crucial to whether a semantic relation is encoded by a DE construction, or which DE construction is selected. Instead, it is information-packaging functions, construals of time-stability, and iconic principles that play a dominant role

Advances in De Novo Drug Design : From Conventional to Machine Learning Methods

De novo drug design is a computational approach that generates novel molecular structures from atomic building blocks with no a priori relationships. Conventional methods include structure-based and ligand-based design, which depend on the properties of the active site of a biological target or its known active binders, respectively. Artificial intelligence, including ma-chine learning, is an emerging field that has positively impacted the drug discovery process. Deep reinforcement learning is a subdivision of machine learning that combines artificial neural networks with reinforcement-learning architectures. This method has successfully been em-ployed to develop novel de novo drug design approaches using a variety of artificial networks including recurrent neural networks, convolutional neural networks, generative adversarial networks, and autoencoders. This review article summarizes advances in de novo drug design, from conventional growth algorithms to advanced machine-learning methodologies and high-lights hot topics for further development.Peer reviewe

Automatic Classification of Verb-Direction Constructions In Mandarin Chinese

Processing Multi-Word Expressions (MWEs) presents a challenge for Natural Language Processing (NLP) systems (Sag et al. 2002). In Mandarin Chinese, there are different kinds of MWEs, such as compounding constructions and serial verb constructions containing multiple predicates (Chao 1968). In this project, I will focus on parsing the semantics of a family of constructions called Verb-Direction Constructions (VDCs) in Chinese. Similar to English Verb-Particle Constructions, VDCs include a verb of precondition followed by a directional verb (e.g., na chu (lit &lsquo;take exit&rsquo;) &lsquo;take out&rsquo;). VDC functions include Self-Motion, Caused-Motion, Aspect, Discourse-Connective, and Evidential, among others (Liu et al. 1998). Achieving native speakers&rsquo; interpretation of a language in machine learning systems can support different applications. Inspired by the framework of Sign-Based Construction Grammar (Sag 2012, Michaelis 2009, 2013) as well as Conceptual Metaphor Theory (Lakoff &amp; Johnson 1980, 1998), I conducted three classification tasks. In the first task, I designed a VDC taxonomy, which categorizes distinct functions of VDCs, such as event structures (both causative and non-causative) that involve the movement of an entity through space to a final location. Two versions of the taxonomy were developed and learned. The annotation guideline was mainly based on an analysis of Frame Semantics (Baker, Fillmore, &amp; Lowe 1998) for different VDC events. In the second task, VDCs were annotated as metaphoric and literal expressions, and metaphor detection was performed. The third task makes preliminary steps aimed at detecting the coerced use of VDCs, in which VDCs alter the canonical argument structures of verbs (Goldberg 1995, 1999). This research makes two primary contributions. First, it establishes linguistic analyses of the VDC properties in question, including taxonomies of event types, metaphorical mappings, and coercion, most of which directly support the VDC classification tasks. Second, based on the linguistically motivated categories, it develops an automated method for semantic classification of VDC constructions, surpassing the scope of classification resources previously devised within Chinese NLP (Xue et al. 2000; Xue &amp; Palmer 2009; Huang et al. 2010; Lu &amp; Wang 2017). The system developed potentially supports other NLP applications, such as machine translation, event detection, metaphor processing, and word sense disambiguation.</p