Data Driven Approach to Networks and Language

The first aim of this workshop is to enhance our understanding of the links between individuals, social structure, and language usage. These questions should be addressed by the detailed analysis of recently available large digital datasets, like ones collected in Twitter and other systems. These datasets include the social interactions and the utterances of a large number of individuals, which allows for the coupled analysis of the social network and language variation and change as a function of time. Our goal is to contribute to the interdisciplinary fields of computational sociolinguistics, network science, data-driven and computational approaches to language and social network. We will bring together researchers focusing on network linguistics, from different fields: machine learning, data analytics, data mining, computational modeling, large-scale graph-structured high-dimensional data, low-dimensional representations by dimensionality reduction. A second objective of 

the workshop will be to discuss about these types of methods, which follow often from a data driven approach, especially for their application to social media dataset.