An examination of cross-cultural similarities and differences from social media data with respect to language use

Abstract

This thesis presents a methodology for analyzing cross-cultural similarities and differences using language as a medium, love as domain, social media as a data source and 'Terms' (emotions and sentiments) and 'Topics' as cultural features. The approach required in order to conduct the study involved the preparation of the corpus from the social media using the methods and techniques of mrpns lingnistks Following this, emotions were extracted from the corpus using Natural Language Processing (NLP) techniques and existing emotion corpus and latent topics of love discussion were then extracted from the corpus using the unsupervised machine learning technique, Latent Dirichlet Allocation (LDA) (Blei et al., 2003). Finally, on the basis of these features, a cross-cultural comparison was carried out. For the purposes of cross-cultural analysis, the experimental focus was placed on comparing data from a culture from the East (India) with a culture from the West (United States of America) with respect to similarities and differences with respect to the usage of emotions, their intensities and topics used during love discussion in social media.