P. H. Patel

In natural language processing (NLP), named entity recognition (NER) and semantic classification are essential tasks. NER is a fundamental task, that identify named entities in text such as people, organizations, and locations. In Legal domain, NER is particularly important due to the variety of named entities that appear in legal documents and are important for legal analysis whereas Semantic classification is the process of giving each sentence in a text a semantic label, such as ”fact,””arguments,” or”judgement”. Both NER and Semantic classi- fication are critical component of many NLP applications such as Knowledge base construction and semantic search. Semantic searching of legal documents is a powerful technique that can be used to quickly find the information that you need. By combining NER and semantic classification, one can identify the key elements of a legal document and search for documents that are related to a particular topic or contain a particular type of information. This paper proposes a novel approach to NER and Semantic classification in legal domain using Long short-term memory (LSTM) model. The proposed approach is evaluated on a corpus of legal text and the result of this study suggest that LSTM models are a promising approach for NER and Semantic classification in legal domain and can be used to improve the performance of semantic searching of legal documents.

So far, most ethical consumerism research has been contained within Western countries, thus limiting our understanding of the concept in emerging markets. Given the call for extending empirical-based knowledge for a better understanding of peculiarities, dynamics and country-level variations (i.e. social, cultural) in the context of ethical consumerism in emerging markets, this research cross-examines the interactive nature of individual- and country-level predictors of ethical consumerism in emerging and developed markets, employing a multilevel approach. At the individual level, we posit that ethical consumerism is motivated by social and cultural capital. In contrast, at the contextual level, we choose country-level affluence as an influential factor that might impact the relationship between socio-cultural capital and ethical consumerism. The study uses the International Social Survey Programme’s (ISSP) 2014 citizenship module data set (including 34 countries) for investigating individual-level predictors (of social and cultural capital). The GDP per capita data from the International Monetary Fund’s (IMF) Economic Outlook database was used to examine the cross-level interactions between individual-level predictors and country-level affluence. The findings suggest that social and cultural capitals positively influence ethical consumerism in emerging and developed markets. Further, country-level affluence moderates the relationship between socio-cultural capital and ethical consumerism for both markets. However, cultural capital proved to be a stronger predictor of ethical consumerism as country-level affluence increases. The research findings highlight meaningful cross-country-level interactions that help further understand the basis of ethical consumerism from a global perspective.