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Corpus linguistics has much to offer history, being as both disciplines engage so heavily in analysis of large amounts of textual material. This book demonstrates the opportunities for exploring corpus linguistics as a method in historiography and the humanities and social sciences more generally. Focusing on the topic of prostitution in 17th-century England, it shows how corpus methods can assist in social research, and can be used to deepen our understanding and comprehension. McEnery and Baker draw principally on two sources – the newsbook Mercurius Fumigosis and the Early English Books Online Corpus. This scholarship on prostitution and the sex trade offers insight into the social position of women in history

Comunicació presentada al BIR 2021: 11th International Workshop on Bibliometric-enhanced Information Retrieval, celebrat l'1 d'abril de 2021 de manera virtual. ; In this work we propose to tackle the limitations posed by the lack of annotated data for argument mining in scientific texts by annotating argumentative units and relations in research abstracts in two scientific domains. We evaluate our annotations by computing inter-annotator agreements, which range from moderate to substantial according to the difficulty level of the tasks and domains. We use our newly annotated corpus to fine-tune BERT-based models for argument mining in single and multi-task settings, finally exploring the adaptation of models trained in one scientific discipline (computational linguistics) to predict the argumentative structure of abstracts in a different one (biomedicine). ; This work was (partly) supported by the Spanish Government under the María de Maeztu Units of Excellence Programme (MDM-2015-0502) and by the Research and Innovation Agency of Uruguay (ANII). We also acknowledge support from the project Context-aware Multilingual Text Simplification (ConMuTeS) PID2019-109066GB-I00/AEI/10.13039/501100011033 awarded by Ministerio de Ciencia, Innovación y Universidades (MCIU) and by Agencia Estatal de Investigación (AEI) of Spain.

Scholars have long established the importance of the cultural outcomes of social movements in the context of political power and representation. However, they have also acknowledged the methodo-logical difficulties associated with studying cultural outcomes, especially when culture is manifested through linguistic practices. This paper addresses the potential for dealing with movements and culture as mani-fested in symbols, public discourse, narratives, and rhetoric and makes two contributions: It links the social movement literature studying culture through language with Natural Language Processing (NLP) techniques for systematic and comprehensive cultural analysis; and introduces a state-of the-art method which pro-vides a better understanding of language change and linguistic influence given the capacity of computa-tional analyses to process large volumes of data for multiple actors and varied data sources during long pe-riods of time. The paper describes the cultural influence of women organizations in Spain between 2000-2020 on issues such as gender inequalities, abortion, gender violence, prostitution, and surrogacy. Tweets and manifestos by women's organizations', as well as national press coverage of women issues and inter-ventions by MPs in the parliamentary arena, are used to describe the advantages and limitations of the method for the study of cultural outcomes. Computational linguistics provides new possibilities for scholarly research on cultural outcomes of social movements but also shows that these methods should be accompa-nied by precise definitions of cultural outcomes, detailed and replicable operationalisation processes, and theoretical models that identify the mechanisms that explain the linguistic phenomena that underly cultural change.

Carbon taxes evoke a variety of public responses, often with negative implications for policy support, implementation, and stringency. Here we use topic modeling to analyze associations of Spanish citizens with a policy proposal to introduce a carbon tax. This involves asking two key questions, to elicit (1) citizens' associations with a carbon tax and (2) their judgment of the fairness of such a policy for distinct uses of tax revenues. We identify 11 topics for the first question and 18 topics for the second. We perform regression analysis to assess how respondents' associations relate to their carbon tax acceptability, knowledge, and sociodemographic characteristics. The results show that, compared to people accepting the carbon tax, those rejecting it show less trust in politicians, think that the rich should pay more than the poor, consider the tax to be less fair, and stress more a lack of renewable energy or low-carbon transport. Respondents accepting a carbon tax emphasize more the need to solve environmental problems and care about a just society. These insights can help policymakers to improve the design and communication of climate policy with the aim to increase its public acceptability. © 2020, Springer Nature B.V. ; This work was funded by a Recercaixa 2016 project titled "understanding Societal Views on Carbon Pricing" and an ERC Advanced Grant from the European Research Council (ERC) under the European Union's Horizon 2020 Research and Innovation Programme (grant agreement no. 741087). I.S. acknowledges financial support from the Russian Science Foundation (RSF grant number 19-18-00262).

Unidad de excelencia María de Maeztu CEX2019-000940-M ; Carbon taxes evoke a variety of public responses, often with negative implications for policy support, implementation and stringency. Here we use topic modelling to analyze associations of Spanish citizens with a policy proposal to introduce a carbon tax. This involves asking two key questions, to elicit (1) citizens' associations with a carbon tax and (2) their judgment of the fairness of such a policy for distinct uses of tax revenues. We identify 11 topics for the first question and 18 topics for the second. We perform regression analysis to assess how respondents' associations relate to their carbon-tax acceptability, knowledge and socio-demographic characteristics. The results show that, compared to people accepting the carbon tax, those rejecting it show less trust in politicians, think that the rich should pay more than the poor, consider the tax to be less fair, and stress more a lack of renewable energy or low-carbon transport. Respondents accepting a carbon tax emphasize more the need to solve environmental problems and care about a just society. These insights can help policy makers to improve the design and communication of climate policy with the aim to increase its public acceptability.

The success of modern software for natural language processing impresses. Programs for orthography and grammar correction, information retrieval from document databases, and translation from one natural language into another, among others, are sold worldwide in millions of copies nowadays. The relationship of the Arabic language to the computer in the process by which the learner acquires the capacity to perceive and comprehend language (in other words, gain the ability to be aware of language and to understand it), as well as to produce and use words and sentences to automated communication