CLARIN

The book provides a comprehensive overview of the Common Language Resources and Technology Infrastructure – CLARIN – for the humanities. It covers a broad range of CLARIN language resources and services, its underlying technological infrastructure, the achievements of national consortia, and challenges that CLARIN will tackle in the future. The book is published 10 years after establishing CLARIN as an Europ. Research Infrastructure Consortium

Digital Methods in the Humanities

Digital Humanities is a transformational endeavor that not only changes the perception, storage, and interpretation of information but also of research processes and questions. It also prompts new ways of interdisciplinary communication between humanities scholars and computer scientists. This volume offers a unique perspective on digital methods for and in the humanities. It comprises case studies from various fields to illustrate the challenge of matching existing textual research practices and digital tools. Problems and solutions with and for training tools as well as the adjustment of research practices are presented and discussed with an interdisciplinary focus

MODELING THE LEADERSHIP OF LANGUAGE CHANGE FROM DIACHRONIC TEXT

Natural languages constantly change over time. These changes are modulated by social factors such as influence which are not always directly observable. However, large-scale computational modeling of language change using timestamped text can uncover the latent organization and social structure. In turn, the social dynamics of language change can potentially illuminate our understanding of innovation, influence, and identity: Who leads? Who follows? Who diverges? This thesis contributes to the growing body of research on using computational methods to model language change with a focus on quantifying linguistic leadership of change. A series of studies highlight the unique contributions of this thesis: methods that scale to huge volumes of data; measures that quantify leadership at the level of individuals or in aggregate; and analysis that links linguistic leadership to other forms of influence. First, temporal and predictive models of event cascades on a network of millions of Twitter users are used to show that lexical change spreads in the form of a contagion and influence from densely embedded ties is crucial for the adoption of non-standard terms. A Granger-causal test for detecting social influence in event cascades on a network is then presented, which is robust to both the presence of confounds such as homophily and can be applied to model both linguistic or non-linguistic change in a network. Next, a novel scheme to score and identify documents that lead semantic change in progress is introduced. This linguistic measure of influence on the documents is strongly predictive of their influence in terms of the number of citations that they receive for both US court opinions and scientific articles. Subsequently, a measure of lead on any semantic change between a pair of document sources (e.g. newspapers) and a method to aggregate multiple lead-lag relationships into a network is presented. Analysis on an induced network of nineteenth century abolitionist newspapers, following the proposed method, reveals the important yet understated role of women and Black editors in shaping the discourse on abolitionism. Finally, a method to induce an aggregate semantic leadership network using contextual word representations is proposed to investigate the link between semantic leadership and influence in the form of citations among publication venues that are part of the Association of Computational Linguistics. Taken together, these studies illustrate the utility of finding leaders of language change to gain insights in sociolinguistics and for applications in social science and digital humanities.Ph.D