Big Textual Data: Lessons and Challenges for Statistics

At issue are a few early stage case studies relating to: research publishing and research impact; literature, narrative and foundational emotional tracking; and social media, here Twitter, with a social science orientation. Central relevance and
importance will be associated with the following aspects of analytical methodology: context, leading to availing of semantics; focus, motivating homology between fields of analytical orientation; resolution scale, which can incorporate a concept hierarchy and aggregation in general; and acknowledging all that is implied by this expression: correlation is not causation. Application areas are: research publishing and qualitative assessment, narrative analysis and assessing impact, and baselining and contextualizing, statistically and in related aspects such as visualization.